Does This App Respect My Privacy? Design and Evaluation of Information Materials Supporting Privacy-Related Decisions of Smartphone Users

Over the years, the wide-spread usage of smartphones leads to large amounts of personal data being stored by them. These data, in turn, can be accessed by the apps installed on the smartphones, and potentially misused, jeopardizing the privacy of smartphone users. While the app stores provide indicators that allow an estimation of the privacy risks of individual apps, these indicators have repeatedly been shown as too confusing for the lay users without technical expertise. We have developed an information flyer with the goal of providing decision support for these users and enabling them make more informed decisions regarding their privacy upon choosing and installing smartphone apps. Our flyer is based on previous research in mental models of smartphone privacy and security and includes heuristics for choosing privacy-friendlier apps used by IT-Security experts. It also addresses common misconceptions of users regarding smartphones. The flyer was evaluated in a user study. The results of the study show, that the users who read the flyer tend to take privacy-relevant factors into account by relying on the heuristics in the flyer more often. Hence, the flyer succeeds in supporting users in making more informed privacy-related decisions

Genome-wide meta-analysis of common variant differences between men and women

The male-to-female sex ratio at birth is constant across world populations with an average of 1.06 (106 male to 100 female live births) for populations of European descent. The sex ratio is considered to be affected by numerous biological and environmental factors and to have a heritable component. The aim of this study was to investigate the presence of common allele modest effects at autosomal and chromosome X variants that could explain the observed sex ratio at birth. We conducted a large-scale genome-wide association scan (GWAS) meta-analysis across 51 studies, comprising overall 114 863 individuals (61 094 women and 53 769 men) of European ancestry and 2 623 828 common (minor allele frequency >0.05) single-nucleotide polymorphisms (SNPs). Allele frequencies were compared between men and women for directly-typed and imputed variants within each study. Forward-time simulations for unlinked, neutral, autosomal, common loci were performed under the demographic model for European populations with a fixed sex ratio and a random mating scheme to assess the probability of detecting significant allele frequency differences. We do not detect any genome-wide significant (P < 5 × 10−8) common SNP differences between men and women in this well-powered meta-analysis. The simulated data provided results entirely consistent with these findings. This large-scale investigation across ∼115 000 individuals shows no detectable contribution from common genetic variants to the observed skew in the sex ratio. The absence of sex-specific differences is useful in guiding genetic association study design, for example when using mixed controls for sex-biased trait

Does This App Respect My Privacy? Design and Evaluation of Information Materials Supporting Privacy-Related Decisions of Smartphone Users

Over the years, the wide-spread usage of smartphones leads to large amounts of personal data being stored by them. These data, in turn, can be accessed by the apps installed on the smartphones, and potentially misused, jeopardizing the privacy of smartphone users. While the app stores provide indicators that allow an estimation of the privacy risks of individual apps, these indicators have repeatedly been shown as too confusing for the lay users without technical expertise. We have developed an information flyer with the goal of providing decision support for these users and enabling them make more informed decisions regarding their privacy upon choosing and installing smartphone apps. Our flyer is based on previous research in mental models of smartphone privacy and security and includes heuristics for choosing privacy-friendlier apps used by IT-security experts. It also addresses common misconceptions of users regarding smartphones. The flyer was evaluated in a user study. The results of the study show, that the users who read the flyer tend to take privacy-relevant factors into account by relying on the heuristics in the flyer more often. Hence, the flyer succeeds in supporting users in making more informed privacy-related decisions

Establishing Long-Term Efficacy in Chronic Disease: Use of Recursive Partitioning and Propensity Score Adjustment to Estimate Outcome in MS

Context: Establishing the long-term benefit of therapy in chronic diseases has been challenging. Long-term studies require non-randomized designs and, thus, are often confounded by biases. For example, although disease-modifying therapy in MS has a convincing benefit on several short-term outcome-measures in randomized trials, its impact on long-term function remains uncertain.ObjectivE: Data from the 16-year Long-Term Follow-up study of interferon-beta-1b is used to assess the relationship between drug-exposure and long-term disability in MS patients.Design/Setting: To mitigate the bias of outcome-dependent exposure variation in non-randomized long-term studies, drug-exposure was measured as the medication-possession-ratio, adjusted up or down according to multiple different weighting-schemes based on MS severity and MS duration at treatment initiation. A recursive-partitioning algorithm assessed whether exposure (using any weighing scheme) affected long-term outcome. The optimal cut-point that was used to define “high” or “low” exposure-groups was chosen by the algorithm. Subsequent to verification of an exposure-impact that included all predictor variables, the two groups were compared using a weighted propensity-stratified analysis in order to mitigate any treatment-selection bias that may have been present. Finally, multiple sensitivity-analyses were undertaken using different definitions of long-term outcome and different assumptions about the data.Main Outcome Measure: Long-Term Disability.Results: In these analyses, the same weighting-scheme was consistently selected by the recursive-partitioning algorithm. This scheme reduced (down-weighted) the effectiveness of drug exposure as either disease duration or disability at treatment-onset increased. Applying this scheme and using propensity-stratification to further mitigate bias, high-exposure had a consistently better clinical outcome compared to low-exposure (Cox proportional hazard ratio = 0.30–0.42; pConclusions: Early initiation and sustained use of interferon-beta-1b has a beneficial impact on long-term outcome in MS. Our analysis strategy provides a methodological framework for bias-mitigation in the analysis of non-randomized clinical data.Trial Registration: Clinicaltrials.gov NCT00206635</p

Genome-wide meta-analysis of common variant differences between men and women

The male-to-female sex ratio at birth is constant across world populations with an average of 1.06 (106 male to 100 female live births) for populations of European descent. The sex ratio is considered to be affected by numerous biological and environmental factors and to have a heritable component. The aim of this study was to investigate the presence of common allele modest effects at autosomal and chromosome X variants that could explain the observed sex ratio at birth. We conducted a large-scale genome-wide association scan (GWAS) meta-analysis across 51 studies, comprising overall 114 863 individuals (61 094 women and 53 769 men) of European ancestry and 2 623 828 common (minor allele frequency 0.05) single-nucleotide polymorphisms (SNPs). Allele frequencies were compared between men and women for directly-typed and imputed variants within each study. Forward-time simulations for unlinked, neutral, autosomal, common loci were performed under the demographic model for European populations with a fixed sex ratio and a random mating scheme to assess the probability of detecting significant allele frequency differences. We do not detect any genome-wide significant (P 5 10(8)) common SNP differences between men and women in this well-powered meta-analysis. The simulated data provided results entirely consistent with these findings. This large-scale investigation across approximate to 115 000 individuals shows no detectable contribution from common genetic variants to the observed skew in the sex ratio. The absence of sex-specific differences is useful in guiding genetic association study design, for example when using mixed controls for sex-biased traits