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The current (and future) adoption of the IoT has, for some time, stimulated debate about the broader implications for privacy, ethics, trust and security that the IoT. Given the IoT's penchant for generating and utilising various (oftentimes somewhat personal) data, the European Union's (EU) forthcoming General Data Protection Regulations (GDPR) will have a significant impact on how the IoT is regulated. As with the term IoT the interpretation of GDPR is generating its own discourses particularly around how wording within the regulation is turned into implementation. The paper begins by critiquing the term Privacy by Design (PbD), and an alternate form which appears in article 25 of the GDPR Data protection by design and default. We note that these two phrases are in fact part of a broader group which inexhaustively includes: Security by Design, Privacy by Default, Security by Default, Data Protection by Design, Data Protection by Default. Our critique does not concern the sentiments or intentions represented by these phrases, or PbD per se, but highlights ambiguities and potentially misleading interpretations that their invocation promotes. After exploring these potential pitfalls, we go on to discuss design-led research that positions Informed by Design as a more fruitful approach to creating IoT devices and services which can more meaningfully respond to concerns about privacy, ethics, trust and security.

<b><i>Background/Aims:</i></b> We compared the 6-Point Scale, a screening tool to identify low-income women for referral to genetic counseling, with genetic counselors' (GCs') recommendation and the Referral Screening Tool (RST). <b><i>Methods:</i></b> RST and 6-Point Scale scores were computed for 2 samples: (1) S1, public hospital mammography clinic patients in 2006-2010 (<i>n</i> = 744), classified by GCs as high risk (meriting referral to counseling) or not high risk, and (2) S2, primary care patients enrolled in an education intervention study in 2011-2012 (<i>n</i> = 1,425). Sensitivity, specificity, and area under the ROC curve (AUROC) were computed for the 6-Point Scale score versus GC and RST classification as high risk. <b><i>Results:</i></b> The 6-Point Scale had low sensitivity (0.27, 95% confidence interval [CI] 0.21-0.34) but high specificity (0.97, 95% CI 0.95-0.99) and AUROC (0.85, 95% CI 0.81-0.90) versus GC classification, and high sensitivity (S1: 0.90, 95% CI 0.79-1.00; S2: 0.94, 95% CI 0.87-0.97), specificity (S1: 0.95, 95% CI 0.93-0.97; S2: 0.94, 95% CI 0.93-0.96), and AUROC (S1: 0.98, 95% CI 0.96-0.99; S2: 0.98, 95% CI 0.98-0.99) versus the RST. <b><i>Conclusion:</i></b> The 6-Point Scale compared favorably with the RST, a validated instrument, and is potentially useful as a simple tool for administration in a safety net setting, requiring minimal time investment by primary care physicians and their staff and no financial investment in tablet computers or software.

Introduction: Research on the perceived utility of genomic sequencing has focused primarily on pediatric populations and on individuals and families with rare genetic diseases. Here, we evaluate how well a multifaceted perceived utility model developed with these populations applies to a diverse, adult population aged 18–49 at risk for hereditary cancer and propose new considerations for the model. Methods: Participants received clinical genomic sequencing in the Cancer Health Assessments Reaching Many (CHARM) study. Semi-structured qualitative interviews were conducted with a subset of participants at 1 and 6 months after results disclosure. We used an approach influenced by grounded theory to examine perceptions of the utility of genomic sequencing and analyzed how utility in CHARM mapped to the published multifaceted perceived utility model, noting which domains were represented or absent and which were most salient to our population. Results: Participants' discussions of utility often involved multiple domains and revealed the variety of ways in which receiving sequencing results can impact one's life. Results demonstrated that an individual's perception of utility can change over the life course when sequenced at a relatively young age and may be influenced by the resources available to them to act on the results. Conclusion: Our findings demonstrate the relevance of a multifaceted perceived utility model for a diverse adult population at risk for hereditary cancer. We identified refinements that could make the model more robust, including emphasizing the overlapping nature of the domains and the importance of life stage and personal resources to the perception of utility.

INTRODUCTION: Implementation of genome-scale sequencing in clinical care has significant challenges: the technology is highly dimensional with many kinds of potential results, results interpretation and delivery require expertise and coordination across multiple medical specialties, clinical utility may be uncertain, and there may be broader familial or societal implications beyond the individual participant. Transdisciplinary consortia and collaborative team science are well poised to address these challenges. However, understanding the complex web of organizational, institutional, physical, environmental, technologic, and other political and societal factors that influence the effectiveness of consortia is understudied. We describe our experience working in the Clinical Sequencing Evidence-Generating Research (CSER) consortium, a multi-institutional translational genomics consortium. METHODS: A key aspect of the CSER consortium was the juxtaposition of site-specific measures with the need to identify consensus measures related to clinical utility and to create a core set of harmonized measures. During this harmonization process, we sought to minimize participant burden, accommodate project-specific choices, and use validated measures that allow data sharing. RESULTS: Identifying platforms to ensure swift communication between teams and management of materials and data were essential to our harmonization efforts. Funding agencies can help consortia by clarifying key study design elements across projects during the proposal preparation phase and by providing a framework for data sharing data across participating projects. CONCLUSIONS: In summary, time and resources must be devoted to developing and implementing collaborative practices as preparatory work at the beginning of project timelines to improve the effectiveness of research consortia.