Improving sustainable transportation options will help cities tackle growing challenges related to population health, congestion, climate change and inequity. Interventions supporting active transportation face many practical and political hurdles. Implementation science aims to understand how interventions or policies arise, how they can be translated to new contexts or scales and who benefits. Sustainable transportation interventions are complex, and existing implementation science frameworks may not be suitable. To apply and adapt implementation science for healthy cities, we have launched our mixed-methods research programme, CapaCITY/É. We aim to understand how, why and for whom sustainable transportation interventions are successful and when they are not.

Across nine Canadian municipalities and the State of Victoria (Australia), our research will focus on two types of sustainable transportation interventions: all ages and abilities bicycle networks and motor vehicle speed management interventions. We will (1) document the implementation process and outcomes of both types of sustainable transportation interventions; (2) examine equity, health and mobility impacts of these interventions; (3) advance implementation science by developing a novel sustainable transportation implementation science framework and (4) develop tools for scaling up and scaling out sustainable transportation interventions. Training activities will develop interdisciplinary scholars and practitioners able to work at the nexus of academia and sustainable cities.

This study received approval from the Simon Fraser University Office of Ethics Research (H22-03469). A Knowledge Mobilization Hub will coordinate dissemination of findings via a website; presentations to academic, community organisations and practitioner audiences; and through peer-reviewed articles.

For artificial intelligence (AI) to help improve mental healthcare, the design of data-driven technologies needs to be fair, safe, and inclusive. Participatory design can play a critical role in empowering marginalised communities to take an active role in constructing research agendas and outputs. Given the unmet needs of the LGBTQI+ (Lesbian, Gay, Bisexual, Transgender, Queer and Intersex) community in mental healthcare, there is a pressing need for participatory research to include a range of diverse queer perspectives on issues of data collection and use (in routine clinical care as well as for research) as well as AI design. Here we propose a protocol for a Delphi consensus process for the development of PARticipatory Queer AI Research for Mental Health (PARQAIR-MH) practices, aimed at informing digital health practices and policy.

The development of PARQAIR-MH is comprised of four stages. In stage 1, a review of recent literature and fact-finding consultation with stakeholder organisations will be conducted to define a terms-of-reference for stage 2, the Delphi process. Our Delphi process consists of three rounds, where the first two rounds will iterate and identify items to be included in the final Delphi survey for consensus ratings. Stage 3 consists of consensus meetings to review and aggregate the Delphi survey responses, leading to stage 4 where we will produce a reusable toolkit to facilitate participatory development of future bespoke LGBTQI+–adapted data collection, harmonisation, and use for data-driven AI applications specifically in mental healthcare settings.

PARQAIR-MH aims to deliver a toolkit that will help to ensure that the specific needs of LGBTQI+ communities are accounted for in mental health applications of data-driven technologies. The study is expected to run from June 2024 through January 2025, with the final outputs delivered in mid-2025. Participants in the Delphi process will be recruited by snowball and opportunistic sampling via professional networks and social media (but not by direct approach to healthcare service users, patients, specific clinical services, or via clinicians’ caseloads). Participants will not be required to share personal narratives and experiences of healthcare or treatment for any condition. Before agreeing to participate, people will be given information about the issues considered to be in-scope for the Delphi (eg, developing best practices and methods for collecting and harmonising sensitive characteristics data; developing guidelines for data use/reuse) alongside specific risks of unintended harm from participating that can be reasonably anticipated. Outputs will be made available in open-access peer-reviewed publications, blogs, social media, and on a dedicated project website for future reuse.