Weaving a web: subaltern consumers, rising consumer culture, and television

Cultivation analysis suggests that television influences local cultures through its complex repertoire of images and narratives, which constitute a representation. Through a discursive analysis of television content in India we contend that rising material aspirations and consumer culture are significantly influenced by this medium. Dialectics of turmoil and tranquility mark this development for the working class population. On the one hand, there is domestication of unrest among subaltern groups, as they withdraw from collective political struggles to narrower and more tranquil forms of emulation and economism. On the other hand, these attempts at emulation have resulted in the poorer sections of society devoting their limited resources to aping a lifestyle well beyond their reach and further compromising their quality of life. The other pole of the dialectic is the increase in turmoil that results from tearing the traditional social fabric and support systems. This turmoil progressively manifests itself in increasing materialism and greater monetization of relationships for these subaltern groups.

A suite of visual languages for model-driven development of statistical surveys and services

Objective: To provide statistician end users with a visual language environment for complex statistical survey design and implementation. Methods: We have developed, in conjunction with professional statisticians, the Statistical Design Language (SDL), an integrated suite of visual languages aimed at supporting the process of designing statistical surveys, and its support environment, SDLTool. SDL comprises five diagrammatic notations: survey diagrams, data diagrams, technique diagrams, task diagrams and process diagrams. SDLTool provides an integrated environment supporting design, coordination, execution, sharing and publication of complex statistical survey techniques as web services. SDLTool allows association of model components with survey artefacts, including data sets, metadata, and statistical package analysis scripts, with the ability to execute elements of the survey design model to implement survey analysis. Results: We describe three evaluations of SDL and SDLTool: use of the notation by expert statistician to design and execute surveys; useability evaluation of the environment; and assessment of several generated statistical analysis web services. Conclusion: We have shown the effectiveness of SDLTool for supporting statistical survey design and implementation. Practice implications: We have developed a more effective approach to supporting statisticians in their survey design work.

An analytical model for web-warping in variable width flexible roll forming

The development of ultra/advanced high strength steels (U/AHSS) has challenged traditional forming methods due to their higher strength and reduced formability. An alternative method is flexible roll forming, which allows the manufacture of sheet metal of high strength and limited ductility into complex and weight-optimized components. However, one major problem in flexible roll forming is the web-warping defect, which is the deviation in height of the web over the length of the profile. The authors’ previous work developed an analytical model to predict the magnitude of web-warping. That model was purely geometric and neglected the effect of material properties. This work develops an analytical solution for the prediction of web-warping that considers both geometric and material parameters. The model results were validated by comparison with numerical and experimental results. The impact of this new model will be the ability to provide a rapid initial design assessment before an intensive numerical analysis of flexible roll forming is conducted.

Design and baseline characteristics of the Food4Me study: a web-based randomised controlled trial of personalised nutrition in seven European countries

Improving lifestyle behaviours has considerable potential for reducing the global burden of non-communicable diseases, promoting better health across the life-course and increasing well-being. However, realising this potential will require the development, testing and implementation of much more effective behaviour change interventions than are used conventionally. Therefore, the aim of this study was to conduct a multi-centre, web-based, proof-of-principle study of personalised nutrition (PN) to determine whether providing more personalised dietary advice leads to greater improvements in eating patterns and health outcomes compared to conventional population-based advice. A total of 5,562 volunteers were screened across seven European countries; the first 1,607 participants who fulfilled the inclusion criteria were recruited into the trial. Participants were randomly assigned to one of the following intervention groups for a 6-month period: Level 0-control group-receiving conventional, non-PN advice; Level 1-receiving PN advice based on dietary intake data alone; Level 2-receiving PN advice based on dietary intake and phenotypic data; and Level 3-receiving PN advice based on dietary intake, phenotypic and genotypic data. A total of 1,607 participants had a mean age of 39.8 years (ranging from 18 to 79 years). Of these participants, 60.9 % were women and 96.7 % were from white-European background. The mean BMI for all randomised participants was 25.5 kg m(-2), and 44.8 % of the participants had a BMI ≥ 25.0 kg m(-2). Food4Me is the first large multi-centre RCT of web-based PN. The main outcomes from the Food4Me study will be submitted for publication during 2015.

iPrevent®: a tailored, web-based, decision support tool for breast cancer risk assessment and management

We aimed to develop a user-centered, web-based, decision support tool for breast cancer risk assessment and personalized risk management. Using a novel model choice algorithm, iPrevent(®) selects one of two validated breast cancer risk estimation models (IBIS or BOADICEA), based on risk factor data entered by the user. Resulting risk estimates are presented in simple language and graphic formats for easy comprehension. iPrevent(®) then presents risk-adapted, evidence-based, guideline-endorsed management options. Development was an iterative process with regular feedback from multidisciplinary experts and consumers. To verify iPrevent(®), risk factor data for 127 cases derived from the Australian Breast Cancer Family Study were entered into iPrevent(®), IBIS (v7.02), and BOADICEA (v3.0). Consistency of the model chosen by iPrevent(®) (i.e., IBIS or BOADICEA) with the programmed iPrevent(®) model choice algorithm was assessed. Estimated breast cancer risks from iPrevent(®) were compared with those attained directly from the chosen risk assessment model (IBIS or BOADICEA). Risk management interventions displayed by iPrevent(®) were assessed for appropriateness. Risk estimation model choice was 100 % consistent with the programmed iPrevent(®) logic. Discrepant 10-year and residual lifetime risk estimates of >1 % were found for 1 and 4 cases, respectively, none was clinically significant (maximal variation 1.4 %). Risk management interventions suggested by iPrevent(®) were 100 % appropriate. iPrevent(®) successfully integrates the IBIS and BOADICEA risk assessment models into a decision support tool that provides evidence-based, risk-adapted risk management advice. This may help to facilitate precision breast cancer prevention discussions between women and their healthcare providers.

Remotely delivered exercise-based cardiac rehabilitation: design and content development of a novel mHealth platform

BACKGROUND: Participation in traditional center-based cardiac rehabilitation exercise programs (exCR) is limited by accessibility barriers. Mobile health (mHealth) technologies can overcome these barriers while preserving critical attributes of center-based exCR monitoring and coaching, but these opportunities have not yet been capitalized on.

OBJECTIVE: We aimed to design and develop an evidence- and theory-based mHealth platform for remote delivery of exCR to any geographical location.

METHODS: An iterative process was used to design and develop an evidence- and theory-based mHealth platform (REMOTE-CR) that provides real-time remote exercise monitoring and coaching, behavior change education, and social support.

RESULTS: The REMOTE-CR platform comprises a commercially available smartphone and wearable sensor, custom smartphone and Web-based applications (apps), and a custom middleware. The platform allows exCR specialists to monitor patients' exercise and provide individualized coaching in real-time, from almost any location, and provide behavior change education and social support. Intervention content incorporates Social Cognitive Theory, Self-determination Theory, and a taxonomy of behavior change techniques. Exercise components are based on guidelines for clinical exercise prescription.

CONCLUSIONS: The REMOTE-CR platform extends the capabilities of previous telehealth exCR platforms and narrows the gap between existing center- and home-based exCR services. REMOTE-CR can complement center-based exCR by providing an alternative option for patients whose needs are not being met. Remotely monitored exCR may be more cost-effective than establishing additional center-based programs. The effectiveness and acceptability of REMOTE-CR are now being evaluated in a noninferiority randomized controlled trial.

Risk management in research and development (R&D) projects: the case of South Australia

A definition of the effective methods of risk management in R&D projects has remained elusive. Similarly, there have been calls to devise effective risk management methods in R&D projects. To develop this area further, the purpose of this study is twofold. First, it validates the veracity of claims about the urgency of introducing effective methods of risk management to R&D projects in South Australia based on nine unstructured interviews with experts. Second, the study presents the outcomes of two case studies that deployed the extended version of the failure mode and effect analysis, namely, the RFMEA method in a South Australian organisation, to investigate how the method can facilitate the identification of effective contingency plans to mitigate high-priority risks. The findings showed that the RFMEA method would be effective for project managers in dealing with risk management issues in R&D projects. The discussions presented will provide guidelines for practitioners in the industry.