How general practitioners and patients discuss type 2 diabetes mellitus and cardiovascular diseases concerns during consultations: Implications for digital health

Objective: To analyse general practitioner–patient consultations about type 2 diabetes mellitus or cardiovascular diseases and describe (i) the nature of self-management discussions; (ii) actions required from patients during and after consultation regarding self-management; and (iii) implications for digital health to support patients during (and after) consultation. Method: This study screened 281 general practitioner consultations conducted in 2017 within the UK general practice setting from an existing dataset containing videos and transcripts of consultations between GPs and patients. Secondary analysis was conducted using a multi-method approach, including descriptive, content, and visualisation analysis, to inform the nature of self-management discussions, what actions are required from patients, and whether digital technology was mentioned during the consultation to support self-management. Results: Analysis of eligible 19 consultations revealed a discord between what self-management actions are required of patients during and after consultations. Lifestyle discussions are often discussed in depth, but these discussions rely heavily on subjective inquiry and recall. Some patients in these cohorts are overwhelmed by self-management, to the detriment of their personal health. Digital support for self-management was not a major topic of discussion, however, we identified a number of emergent gaps where digital technology can support self-management concerns. Conclusion: There is potential for digital technology to reconcile what actions are required of patients during and after consultations. Furthermore, a number of emergent themes around self-management have implications for digitalisation

Implementation of a consumer-focused eHealth intervention for people with moderate-to-high cardiovascular disease risk: protocol for a mixed-methods process evaluation

Technology-mediated strategies have potential to engage patients in modifying unhealthy behaviour and improving medication adherence to reduce morbidity and mortality from cardiovascular disease (CVD). Furthermore, electronic tools offer a medium by which consumers can more actively navigate personal healthcare information. Understanding how, why and among whom such strategies have an effect can help determine the requirements for implementing them at a scale. This paper aims to detail a process evaluation that will (1) assess implementation fidelity of a multicomponent eHealth intervention; (2) determine its effective features; (3) explore contextual factors influencing and maintaining user engagement; and (4) describe barriers, facilitators, preferences and acceptability of such interventions.Methods and analysis: Mixed-methods sequential design to derive, examine, triangulate and report data from multiple sources. Quantitative data from 3 sources will help to inform both sampling and content framework for the qualitative data collection: (1) surveys of patients and general practitioners (GPs); (2) software analytics; (3) programme delivery records. Qualitative data from interviews with patients and GPs, focus groups with patients and field notes taken by intervention delivery staff will be thematically analysed. Concurrent interview data collection and analysis will enable a thematic framework to evolve inductively and inform theory building, consistent with a realistic evaluation perspective. Eligible patients are those at moderate-to-high CVD risk who were randomised to the intervention arm of a randomised controlled trial of an eHealth intervention and are contactable at completion of the follow-up period; eligible GPs are the primary healthcare providers of these patients.Ethics and dissemination: Ethics approval has been received from the University of Sydney Human Research Ethics Committee and the Aboriginal Health and Medical Research Council (AH&MRC) of New South Wales. Results will be disseminated via scientific forums including peer-reviewed publications and national and international conferences

Wild Type and Mutant 2009 Pandemic Influenza A (H1N1) Viruses Cause More Severe Disease and Higher Mortality in Pregnant BALB/c Mice

BACKGROUND: Pregnant women infected by the pandemic influenza A (H1N1) 2009 virus had more severe disease and higher mortality but its pathogenesis is still unclear. PRINCIPAL FINDINGS: We showed that higher mortality, more severe pneumonitis, higher pulmonary viral load, lower peripheral blood T lymphocytes and antibody responses, higher levels of proinflammatory cytokines and chemokines, and worse fetal development occurred in pregnant mice than non-pregnant controls infected by either wild type (clinical isolate) or mouse-adapted mutant virus with D222G substitution in hemagglutinin. These disease-associated changes and the lower respiratory tract involvement were worse in pregnant mice challenged by mutant virus. Though human placental origin JEG-3 cell line could be infected and proinflammatory cytokines or chemokines were elevated in amniotic fluid of some mice, no placental or fetal involvement by virus were detected by culture, real-time reverse transcription polymerase chain reaction or histopathological changes. Dual immunofluorescent staining of viral nucleoprotein and type II alveolar cell marker SP-C protein suggested that the majority of infected alveolar epithelial cells were type II pneumocytes. CONCLUSION: The adverse effect of this pandemic virus on maternal and fetal outcome is largely related to the severe pulmonary disease and the indirect effect of inflammatory cytokine spillover into the systemic circulation

Finishing the euchromatic sequence of the human genome

The sequence of the human genome encodes the genetic instructions for human physiology, as well as rich information about human evolution. In 2001, the International Human Genome Sequencing Consortium reported a draft sequence of the euchromatic portion of the human genome. Since then, the international collaboration has worked to convert this draft into a genome sequence with high accuracy and nearly complete coverage. Here, we report the result of this finishing process. The current genome sequence (Build 35) contains 2.85 billion nucleotides interrupted by only 341 gaps. It covers ∼99% of the euchromatic genome and is accurate to an error rate of ∼1 event per 100,000 bases. Many of the remaining euchromatic gaps are associated with segmental duplications and will require focused work with new methods. The near-complete sequence, the first for a vertebrate, greatly improves the precision of biological analyses of the human genome including studies of gene number, birth and death. Notably, the human enome seems to encode only 20,000-25,000 protein-coding genes. The genome sequence reported here should serve as a firm foundation for biomedical research in the decades ahead

Can cognitive biases during consumer health information searches bereduced to improve decision making?

Objective: To test whether the anchoring and order cognitive biases experienced during search by consumers using information retrieval systems can be corrected to improve the accuracy of, and confidence in, answers to health-related questions. Design: A prospective study was conducted on 227 undergraduate students who used an online search engine developed by the authors to find health information and then answer six randomly assigned consumer health questions. The search engine was fitted with a baseline user interface and two modified interfaces specifically designed to debias anchoring or order effect. Each subject used all three user interfaces, answering two questions with each. Measurements: Frequencies of correct answers pre- and post-search and confidence in answers were collected. Time taken to search and then answer a question, the number of searches conducted and the number of links accessed in a search session were also recorded. User preferences for each interface were measured. Chi-square analyses tested for the presence of biases with each user interface. The Kolmogorov-Smirnov test checked for quality of distribution of the evidence analyzed for each user interface. The test for difference between proportions and the Wilcoxon signed ranks test were used when comparing interfaces. Results: Anchoring and order effects were present amongst subjects using the baseline search interface (anchoring: p < 0.001; order: p = 0.026). With use of the order debiasing interface, the initial order effect was no longer present (p = 0.34) but there was no significant improvement in decision accuracy (p = 0.23). While the anchoring effect persisted when using the anchor debiasing interface (p < 0 .001), its use was associated with a 10.3% increase in subjects who had answered incorrectly pre-search, answering correctly post-search (p = 0.10). Subjects using either debiasing user interface conducted fewer searches and accessed more documents compared to baseline (p <0.001). In addition, the majority of subjects preferred using a debiasing interface over baseline. Conclusion: This study provides evidence that (i) debiasing strategies can be integrated into the user interface of a search engine; (ii) information interpretation behaviors can be to some extent debaised; and that (iii) attempts to debias information searching by consumers can influence their ability to answer health-related questions accurately, their confidence in these answers, as well as the strategies used to conduct searches and retrieve information.23 page(s

Social features in online communities for healthcare consumers - a review

This review provides a snapshot of the literature in online communities for healthcare consumers. It summarizes the features commonly used by healthcare consumers in online communities: seeking and sharing personal experiences, opinions and answers, and exchanging social support. This review also identifies behaviors that are commonly practiced by healthcare consumers but are not readily supported in current online communities. These include collaborative healthcare decision-making, conducting social comparison, and lurking in online communities. This review concludes by emphasizing the importance of trust, privacy and safety when designing an online community for healthcare consumers, particularly in the age of Web 2.0.8 page(s

A Bayesian model that predicts the impact of Web searching on decision-making

This study aimed to develop a model for predicting the impact of information access using Web searches, on human decision making. Models were constructed using a database of search behaviors and decisions of 75 clinicians, who answered questions about eight scenarios within 80 minutes in a controlled setting at a university computer laboratory. Bayesian models were developed with and without bias factors to account for anchoring, primacy, recency, exposure, and reinforcement decision biases. Prior probabilities were estimated from the population prior, from a personal prior calculated from presearch answers and confidence ratings provided by the participants, from an overall measure of willingness to switch belief before and after searching, and from a willingness to switch belief calculated in each individual scenario. The optimal Bayes model predicted user answers in 73.3 % (95 % CI: 68.71 to 77.35%) of cases, and incorporated participants ’ willingness to switch belief before and after searching for each scenario, as well as the decision biases they encounter during the search journey. In most cases, it is possible to predict the impact of a sequence of documents retrieved by a Web search engine on a decision task without reference to the content or structure of the documents, but relying solely on a simple Bayesian model of belief revision

The Influence of crowds on consumer health decisions : an online prospective study

This paper presents an online prospective study investigating whether the strength of social feedback, i.e. the proportion of persons who concur or do not concur with one's own answer to a question, influences the way one answers health-related questions. Two hundred and twenty-seven undergraduate students were recruited to use an online search engine to answer six health-related questions. Subjects recorded their pre- and post-search answers to each question and their level of confidence in these answers. After answering each question post-search, subjects were presented with a summary of post-search answers provided by previous subjects and were asked to answer the question again. There was a statistically significant relationship between the absolute number of others with a different answer (the crowd's opinion volume) and the likelihood of an individual changing an answer (P 50%) of subjects. When subjects had a post-search answer that did not concur with the majority, they were 24% more likely to change answer than those with answers that concurred (P <.0001). This study provides empirical evidence that strength of social feedback influences the way healthcare consumers answer health-related questions.5 page(s

Participatory health through social media

Participatory Health through Social Media explores how traditional models of healthcare can be delivered differently through social media and online games, and how these technologies are changing the relationship between patients and healthcare professionals, as well as their impact on health behavior change. The book also examines how the hospitals, public health authorities, and inspectorates are currently using social media to facilitate both information distribution and collection. Also looks into the opportunities and risks to record and analyze epidemiologically relevant data retrieved from the Internet, social media, sensor data, and other digital sources. The book encompasses topics such as patient empowerment, gamification and social games, and the relationships between social media, health behavior change, and health communication crisis during epidemics. Additionally, the book analyzes the possibilities of big data generated through social media. Authored by IMIA Social Media working group, this book is a valuable resource for healthcare researchers and professionals, as well as clinicians interested in using new media as part of their practice or research. Presents a multidisciplinary point of view providing the readers with a broader perspective Brings the latest case studies and technological advances in the area, supported by an active international community of members who actively work in this area Endorsed by IMIA Social Media workgroup, guaranteeing trustable information from the most relevant experts on the subject Examines how the hospitals, public health authorities, and inspectorates are currently using social media to facilitate both information distribution and collection.138 page(s

From web-based to mobile : experiences of developing a personally controlled health management system

Objective/Aims: Personally controlled health management systems (PCHMS) in mobile technologies offer a new platform for personal health care. The objective of this study was to develop a mobile version of “Healthy.me”, an existing web-based PCHMS, and analyse its usability. Method: The mobile extension of the PCHMS was iteratively designed from its web-based version and evaluated over a period of 6 months. 17 participants completed a 30-minute five-part usability study incorporating the think aloud protocol, task activities, card ranking exercises, interviews, and a technology acceptance questionnaire measuring the “perceived usefulness” and “perceived ease of use” of the mobile version. Results: A mobile version of the PCHMS from its original web-based conception was successfully developed. According to their ratings on the technology acceptance questionnaire, participants found the overall mobile application useful, easy to use, and that there is strong intention to use the mobile application to manage their health. Conclusion: Providing a PCHMS in both web-based and mobile-based platform that is well accepted by consumers should allow more people to have convenient access to their health information, selfmanagement tools and thus improve their overall day-to-day health management. The user experience on smartphone should be carefully considered when transferring a PCHMS from traditional web-based to mobile application.12 page(s