A mixed-methods study exploring women's perceptions and recommendations for a pregnancy app with monitoring tools.

Digital health tools such as apps are being increasingly used by women to access pregnancy-related information. Conducted during the COVID-19 pandemic, this study investigated: (i) pregnant women's current usage of digital health tools to self-monitor and (ii) their interest in theoretical pregnancy app features (a direct patient-to-healthcare-professional communication tool and a body measurement tool). Using a mixed methods approach, 108 pregnant women were surveyed and 15 currently or recently pregnant women were interviewed online. We found that pregnant women used digital health tools to mainly access pregnancy related information and less so to self-monitor. Most participants were interested and enthusiastic about a patient-to-healthcare-professional communication tool. About half of the survey participants (49%) felt comfortable using a body measurement tool to monitor their body parts and 80% of interview participants were interested in using the body measurement to track leg/ankle swelling. Participants also shared additional pregnancy app features that they thought would be beneficial such as a "Digital Wallet" and a desire for a holistic pregnancy app that allowed for more continuous and personalised care. This study highlights the gaps and needs of pregnant women and should inform all stakeholders designing pregnancy digital healthcare. This study offers a unique insight into the needs of pregnant women during a very particular and unique period in human history.

Pregnancy Apps for Self-Monitoring: Scoping Review of the Most Popular Global Apps Available in Australia.

Digital health tools, such as apps, have the potential to promote healthy behaviours, especially self-monitoring, which can facilitate pregnancy management and reduce the risk of associated pregnancy health conditions. While pregnancy apps are popular amongst pregnant women, there is limited information about the overall quality of their content or self-monitoring tools and the number of behaviour change techniques (BCTs) that they include. The aim of this study was thus to assess the quality of pregnancy apps for self-monitoring, and their usage of BCTs. We identified pregnancy apps by web scraping the most popular global apps for self-monitoring in the Apple App Store and Google Play Store available in Australia. The app quality was evaluated using the scorecard approach and the inclusion of BCTs was evaluated using the ABACUS tool. We identified 31 pregnancy apps that met our eligibility criteria. We found that pregnancy apps tended to score the highest in the domains of 'cost and time', 'usability', and 'technical', and lowest on 'clinical' and 'end-user requirements'. Additionally, the majority of apps contained minimal BCTs. Based on our findings, we propose a digital health scorecard visualisation that would break down app quality criteria and present them in a more accessible way to clinicians and pregnant users. We conclude that these findings highlight the shortcomings of available commercial pregnancy apps and the utility of a digital health scorecard visualisation that would empower users to make more informed decisions about which apps are the most appropriate for their needs.

Information and Agreement in the Reputation Game Simulation.

Modern communication habits are largely shaped by the extensive use of social media and other online communication platforms. The enormous amount of available data and speed with which new information arises, however, often suffices to cause misunderstandings, false conclusions, or otherwise disturbed opinion formation processes. To investigate some of these effects we use an agent-based model on gossip and reputation dynamics with 50 agents, including Bayesian knowledge updates under bounded rationality and up to the second-order theory of mind effects. Thereby, we observe the occurrence of reputation boosts from fake images, as well as the advantage of hiding one's opinion in order to become a strong information trader. In addition, the simulations show fundamentally different mechanisms for reaching high agreement with others and becoming well-informed. Additionally, we investigate the robustness of our results with respect to different knowledge-update mechanisms and argue why it makes sense to especially emphasize the margins of distribution when judging a bounded quantity such as honesty in a reputation game simulation.

Can the morphology of γ-ray emission distinguish annihilating from decaying dark matter?

Recent results from the PAMELA, ATIC, FERMI and HESS experiments have focused attention on the possible existence of high energy cosmic rays e+ e- that may originate from dark matter annihilations or decays in the Milky Way. Here we examine the morphology of the associated γ-ray emission after propagation of the electrons generated by both annihilating and decaying dark matter models. We focus on photon energies of 1, 10, and 50 GeV (relevant for the FERMI satellite) and consider different propagation parameters. Our main conclusion is that distinguishing annihilating from decaying dark matter may only be possible if the propagation parameters correspond to the most optimistic diffusion models. In addition, we point to examples where morphology can lead to an erroneous interpretation of the source injection energy.