Accessing adequate healthcare, particularly essential services like physical therapy, presents a significant challenge for individuals with Down syndrome. This demographic often encounters obstacles such as limited accessibility, scarce resources, and a lack of tailored solutions that specifically address their unique needs. The resulting disparity leads to inconsistent care and suboptimal healthcare experiences. Recognizing the importance of eliminating these barriers is crucial to create a more inclusive healthcare environment for individuals with Down syndrome. Rainbow Monster Madness serves as a multifaceted solution to the social determinants of health that significantly impact individuals with Down syndrome. The game's design directly tackles several of these determinants by offering accessible, engaging, and family-centered therapy. In terms of healthcare access and quality, the game empowers parents to actively participate in their child's therapy, ensuring the correct administration of exercises and the consistent provision of quality care. The game's design addresses neighborly and built environment determinants by providing an accessible and inclusive therapy option that can be implemented within the comfort of one's home. This approach fosters a sense of safety and familiarity for children undergoing therapy, promoting a more relaxed and conducive environment. Additionally, Rainbow Monster Madness encourages social community engagement by fostering a collaborative atmosphere between parents and children during therapy sessions. This collaborative approach creates a supportive and engaging environment, positively impacting the overall therapeutic experience. Adhering to the principles of Self-Determination Theory, the game cultivates intrinsic motivation and psychological well-being among children with Down syndrome. This approach enables active engagement in therapy and contributes to their overall health and well-being. The exercises included in Rainbow Monster Madness are carefully selected to cater to the unique needs of individuals with Down syndrome. This regimen combines muscle-strengthening, cardio, and balance exercises, tailored to this specific population. The modification of exercises and thematic design ensures that children remain enthusiastic about their therapy, ultimately promoting better adherence and more effective results. In summary, Rainbow Monster Madness represents a comprehensive solution to the multitude of challenges faced by individuals with Down syndrome in accessing healthcare. Simultaneously, it addresses the broader social determinants of health, thereby fostering a healthier and more inclusive future for this deserving population.

The lack of affordable pharmaceutical access in rural communities is a nationwide crisis for up to 14% of American homes. Pharm to Farm believes that individuals in rural areas deserve the treatment and accessibility that urban and suburban areas receive. Through our approach, we help to bridge this accessibility gap by empowering those marginalized homes to affordably access pharmaceutical health resources. Pharm to Farm achieves this with our business model that allows individuals to get their medications delivered at a cost of only $35 per month.

There is a need for indicators of transportation-land use system quality that are understandable to a wide range of stakeholders, and which can provide immediate feedback on the quality of interactively designed scenarios. Location-based accessibility indicators are promising candidates, but indicator values can vary strongly depending on time of day and transfer wait times. Capturing this variation increases complexity, slowing down calculations. We present new methods for rapid yet rigorous computation of accessibility metrics, allowing immediate feedback during early-stage transit planning, while being rigorous enough for final analyses. Our approach is statistical, characterizing the uncertainty and variability in accessibility metrics due to differences in departure time and headway-based scenario specification. The analysis is carried out on a detailed multi-modal network model including both public transportation and streets. Land use data are represented at high resolution. These methods have been implemented as open-source software running on commodity cloud infrastructure. Networks are constructed from standard open data sources, and scenarios are built in a map-based web interface. We conclude with a case study, describing how these methods were applied in a long-term transportation planning process for metropolitan Amsterdam.

Accessibility is increasingly used as a metric when evaluating changes to public transport systems. Transit travel times contain variation depending on when one departs relative to when a transit vehicle arrives, and how well transfers are coordinated given a particular timetable. In addition, there is necessarily uncertainty in the value of the accessibility metric during sketch planning processes, due to scenarios which are underspecified because detailed schedule information is not yet available. This article presents a method to extend the concept of "reliable" accessibility to transit to address the first issue, and create confidence intervals and hypothesis tests to address the second.