Developing the multi-dimensional mobility divide index (MDI) as a methodology to assess the accessibility level of public transport systems.

Background: This paper presents the development of a multi-dimensional mobility divide index (MDI) for assessing the accessibility of public transport developed using a co-design approach, directly involving end-users in the index design process. The index measures the gap that persons with disabilities feel they need to over-come to use public transport in the same way non-disabled citizens do. The MDI covers six accessibility-related dimensions: 1) safety, 2) convenience, 3) comfort, 4) affordability, 5) travel time, and 6) autonomy. Methods: The method paper describes the step-by-step approach to create the MDI as a set of indicators to be rated by people with different access needs to 1) provide evidence of the main criticalities to be addressed through the design and implementation of new inclusive mobility solutions, 2) guide the design of new inclusive mobility solutions and measure their impacts, and 3) inform the transport sector encouraging positive changes in transport by providing recommendations for policy-making, new directions for service innovation, improvements and practical advice or highlighting investment priorities to pave the way for a more inclusive mobility. Results: We present our findings in ways that can inform universal design and provide actionable information to researchers, policymakers, transport and urban planners, operators, and stakeholders' representatives to promote inclusive and equitable mobility solutions for all. Conclusions: Finally, we suggest follow up research and innovation, as well as recommendations for its uptake and utilisation in the pursuit of European accessibility standards and requirements for products and services in the mobility sector.

Shared mobility services: an accessibility assessment from the perspective of people with disabilities.

Introduction: Shared on-demand mobility services emerge at a fast pace, changing the landscape of public transport. However, shared mobility services are largely designed without considering the access needs of people with disabilities, putting these passengers at risk of exclusion. Recognising that accessibility is best addressed at the design stage and through direct participation of persons with disabilities, the objective of this study was to explore disabled users' views on the following emerging shared mobility services: (a) ride pooling, (b) microtransit, (c) motorbike taxis, (d) robotaxis, (f) e-scooter sharing, and (g) bike sharing. Methodolgy: Using an online mobility survey, we sampled disabled users' (1) views on accessibility, (2) use intention, and (3) suggestions for improving accessibility. The results reflect the responses of 553 individuals with different types of disabilities from 21 European countries. Results: Projected accessibility and use intention were greatest for microtransit, robotaxis, and ride pooling across different disabilities. In contrast, motorbike taxis, e-scooter sharing, and bike sharing were viewed as least accessible and least attractive to use, especially by persons with physical, visual, and multiple disabilities. Despite differences in projected accessibility, none of the shared mobility services would fulfil the access needs of disabled persons in their current form. Suggestions for increasing the accessibility of these services included (a) an ondemand door-to-door service, (b) an accessible booking app, (c) real-time travel information, and (d) the necessity of accommodating wheelchairs. Conclusions: Our findings highlight the need for improving both vehicles and service designs to cater for the access needs of persons with disabilities and provide policymakers with recommendations for the design of accessible mobility solutions.

A reflection on participatory research methodologies in the light of the COVID-19 - lessons learnt from the European Research Project TRIPS.

The coronavirus disease (COVID-19) outbreak has had considerable impacts on research projects, particularly those adopting participatory approaches. This paper reflects on the methodological adaptations employed by the European research project TRIPS to facilitate co-design and open innovation practices towards the development of accessible mobility solutions. The article reports how the methods were adapted to facilitate participatory research with almost no physical meetings. In doing so, the paper presents the alternative 'distanced-based' participatory approaches employed to engage users with disabilities and institutional stakeholders in the transport ecosystem, like online workshops, social media content analysis, online surveys and peer-to-peer telephone interviews. Lessons learnt and practical guidelines for distance-based participatory research are presented and discussed with the aim of increasing resilience in the light of future changes.

Assessing the Privacy of mHealth Apps for Self-Tracking: Heuristic Evaluation Approach.

BACKGROUND: The recent proliferation of self-tracking technologies has allowed individuals to generate significant quantities of data about their lifestyle. These data can be used to support health interventions and monitor outcomes. However, these data are often stored and processed by vendors who have commercial motivations, and thus, they may not be treated with the sensitivity with which other medical data are treated. As sensors and apps that enable self-tracking continue to become more sophisticated, the privacy implications become more severe in turn. However, methods for systematically identifying privacy issues in such apps are currently lacking. OBJECTIVE: The objective of our study was to understand how current mass-market apps perform with respect to privacy. We did this by introducing a set of heuristics for evaluating privacy characteristics of self-tracking services. METHODS: Using our heuristics, we conducted an analysis of 64 popular self-tracking services to determine the extent to which the services satisfy various dimensions of privacy. We then used descriptive statistics and statistical models to explore whether any particular categories of an app perform better than others in terms of privacy. RESULTS: We found that the majority of services examined failed to provide users with full access to their own data, did not acquire sufficient consent for the use of the data, or inadequately extended controls over disclosures to third parties. Furthermore, the type of app, in terms of the category of data collected, was not a useful predictor of its privacy. However, we found that apps that collected health-related data (eg, exercise and weight) performed worse for privacy than those designed for other types of self-tracking. CONCLUSIONS: Our study draws attention to the poor performance of current self-tracking technologies in terms of privacy, motivating the need for standards that can ensure that future self-tracking apps are stronger with respect to upholding users' privacy. Our heuristic evaluation method supports the retrospective evaluation of privacy in self-tracking apps and can be used as a prescriptive framework to achieve privacy-by-design in future apps.