Co-design Model Research Articles

ParaVerse: co-design of a parachute rehearsal and training virtual-reality enhanced simulator for the Australian Defence Force: combining a generative co-design framework and an agile approach to development

While co-design methods are crucial for developing digital educational interventions that are user-centred, contextually relevant, inclusive, and effective in meeting the diverse needs of learners and educators, little attention has been paid to the potential value of co-design processes for digital application development in the Defence context. This research gauged the efficacy of combining a generative co-design framework making use of agile and iterative co-design principles in an applied research and development project. The project produced an immersive virtual reality based digital solution in collaboration with the Australian Defence Force Special Operations Command (SOCOMD) Army. Specifically, the ParaVerse project sought to develop a solution considering the advanced Tactics, Techniques and Procedures (TTPs) relevant to special operations soldiers for advanced parachute training. A Defence advisory group consisting of a series of subject matter experts was formulated to consult with the research and development team over the course of the co-design process. End-user testing with 35 SOCOMD personnel demonstrated the value of the ParaVerse application for SOCOMD personnel, speaking to the success of the leveraged generative co-design model. End-users rated ParaVerse as having greater capacity to influence education and training practices for SOCOMD and Defence generally in comparison to a pre-existing virtual parachute simulator. ParaVerse was also rated higher for satisfaction and useability and was associated with fewer instances of motion sickness. The Generative Co-Design Framework leveraged for this research provides one roadmap on how to integrate end-users in innovation design, particularly for projects working across the nexus of Defence and academia.

Co-Design Model of Support for Child and Family Health Nurse Practice with Culturally and Linguistically Diverse Families

Culturally and linguistically diverse (CALD) mothers with young children face multiple inequities in accessing primary health services, such as language barriers, social isolation, low health literacy, and the availability of appropriate interpretation services. These inequities are persistent and indicate that child and family health nurse (CFHN) services, the providers of primary healthcare in many developed countries, require better support to address the needs of these families. This study engaged with CFHNs and healthcare interpreters to co-design a model of support for practice using workshops that included individual and collective brainstorming and visual representations. Transcripts of the discussion were analysed using thematic analysis. CFHNs and interpreters were able to articulate their perfect service model: a central multidisciplinary team of CFHNs, interpreters, and bilingual educators who could facilitate nurse–interpreter and nurse–interpreter–client relationships, allowing CFHNs and interpreters to do their jobs properly. This central structural component would support and be supported by rapport, trust, client choice and access, continuity of care, and cultural comfort. The study concluded that CALD mothers’ access and engagement require CFHNs to have support for their cultural comfort through the mechanism of bilingual educators and the expansion of healthcare interpreters’ role and scope in working with CFHNs in the delivery of services.

Guiding Diffusion Models for Antibody Sequence and Structure Co-design with Developability Properties

Guiding Diffusion Models for Antibody Sequence and Structure Co-design with Developability Properties

Consumer involvement in health service research: a cross-sectional survey of staff in an Australian public hospital and health service.

ObjectiveConsumer involvement is when patients (their families, friends, and caregivers) work with researchers on research projects. While health services are expected to support consumer-researcher collaborations, conducive environments still need to be developed, with limited research into how Australian health services support this practice. This study explores current consumer involvement in research activity and staff perceptions at an Australian tertiary hospital and health service.MethodsResearch-active employees at a health service were invited to participate in an online cross-sectional survey. It assessed experience with and confidence in involving consumers in research, the perceived value of consumer involvement, and considerations related to challenges, facilitators, and solutions to enhance consumer involvement in health service research.ResultsAmong 83 respondents, including medical, nursing, and allied health professionals, 54 completed the survey. Approximately half had experience with involving consumers in research. Over 80% recognised that involving consumers enhanced research relevance. Identified barriers included challenges in finding (46.6%) and compensating (59.3%) consumers, as well as deficiencies in researcher skills, knowledge (32.2%), and time constraints (39%). Facilitators comprised access to experienced researchers and educational opportunities. Moreover, 87% advocated for increased support to involve consumers within health services, with the appointment of a designated consumer involvement officer deemed the most beneficial solution by 92.5% of respondents.ConclusionsWhile individual barriers inhibit consumer involvement in research, more prominent institutional factors such as financial and technical support may determine successful and meaningful collaborations. As health services evolve towards co-design models in research, the outcomes of this study will guide initiatives aimed at enhancing consumer involvement in the research process within Australian health services.

Co-Design Workshops to Develop a Psychosocial Support Service Model for Refugees in Sweden Affected by Gender-Based Violence.

Experiencing gender-based violence (GBV) is common among refugees. Intersecting systems of oppression can increase the risk of GBV and of suffering detrimental consequences, while concurrently creating barriers to meaningful support. Despite this, refugees with lived experience of GBV are rarely involved in the development, planning and adaptation of services and policies. This article reports on a formative research process that aimed to involve public contributors (refugee victim-survivors of GBV) and relevant stakeholders in co-designing a service model aimed at improving psychosocial support in Sweden. Led by a partnership of public contributors and academic researchers, the research process consisted of iterative cycles of co-design workshops, complemented by scoping of existing literature. The co-design process resulted in a characterisation of the psychosocial service system needs, as perceived by the survivor co-researchers and stakeholders, and a two-level empowerment and support service model. The model included (i) a community-based intervention to promote help-seeking and (ii) psychosocial group support delivered in specialist clinics. Outcomes of the project included perceived benefits for those involved, service-led direct changes and acquisition of funding for continued research on the co-designed model. Improving psychosocial support for refugees in Sweden affected by GBV requires safe spaces to connect with peers and familiarise with available services, laws and rights in the society. Further, strengthened collaborations across sectors are necessary to meet the variety of needs. Co-design workshops were an effective way to initiate changes in the service delivery model for psychosocial support for refugees in Sweden affected by GBV. This is a participatory reflection on a participatory process. The survivor co-researchers contributed to designing and carrying out the PPI process and have co-authored this manuscript.

Cost-Effectiveness and Budget Impact Analysis of an Evidence Based Co-Designed Model of Cardiac Rehabilitation for Patients in Rural and Remote Areas

Cost-Effectiveness and Budget Impact Analysis of an Evidence Based Co-Designed Model of Cardiac Rehabilitation for Patients in Rural and Remote Areas

Supporting the nutrition-related health and well-being of people experiencing socio-economic disadvantage: Findings from a national survey.

People experiencing socio-economic disadvantage face significantly higher rates of diet-related health inequities. This study aimed to explore barriers, opportunities and potential solutions in providing food and nutrition services to people experiencing socio-economic disadvantage from the perspective of services providers. The present study is part of a broad co-design model to improve service provision for people experiencing socio-economic disadvantage. A cross-sectional online survey involving 33 open and closed-ended questions was distributed to Australian governmental and non-governmental organisations providing nutrition-related support to people experiencing socio-economic disadvantage aged 16 years and over. Data were analysed using frequency distributions and conceptual content analyses. Sixty-eight responses were analysed. Services are predominantly offered by charitable organisations (90%), funded through private donations (66%) and reliant on volunteers (100%). Barriers to supporting clients' nutrition needs include financial constraints, limited community engagement, understaffing, insufficient resources and knowledge gaps. Opportunities and solutions for enhancing support include increasing government funding, advocacy initiatives, stronger community collaboration and more holistic, customised services. Proposed recommendations include establishing purpose-built facilities or wrap-around services to expand access to health services, life skills, training and educational programs. Services face challenges including volunteer reliance, limited resources and inadequate government support, hindering food provision. Client barriers include transportation costs and lack of social support. With dedicated financial support, services can offer comprehensive assistance, including community spaces, staffing, health and social services and training. Community partnerships can maximise funding impact. Solutions must address overall well-being and broader social determinants such as income inequality and housing.

Role of depth in optical diffractive neural networks

Free-space all-optical diffractive neural networks have emerged as promising systems for neuromorphic scene classification. Understanding the fundamental properties of these systems is important to establish their ultimate performance. Here we consider the case of diffraction by subwavelength apertures and study the behavior of the system as a function of the number of diffractive layers by employing a co-design modeling approach. We show that adding depth allows the system to achieve high classification accuracies with a reduced number of diffractive features compared to a single layer, but that it does not allow the system to surpass the performance of an optimized single layer. The improvement from depth is found to be limited to the first few layers. These properties originate from the constraints imposed by the physics of light, in particular the weakening electric field with distance from the aperture.

Predictive analytics support for complex chronic medical conditions: An experience-based co-design study of physician managers’ needs and preferences

PurposeThe literature suggests predictive technology applications in health care would benefit from physician and manager input during design and development. The aim was to explore the needs and preferences of physician managers regarding the role of predictive analytics in decision support for patients with the highly complex yet common combination of multiple chronic conditions of cardiovascular (Heart) and kidney (Nephrology) diseases and diabetes (HND). MethodsThis qualitative study employed an experience-based co-design model comprised of three data gathering phases: 1. Patient mapping through non-participant observations informed by process mining of electronic health records data, 2. Semi-structured experience-based interviews, and 3. A co-design workshop. Data collection was conducted with physician managers working at or collaborating with the HND center, Danderyd University Hospital (DSAB), in Stockholm, Sweden. HND center is an integrated practice unit offering comprehensive person-centered multidisciplinary care to stabilize disease progression, reduce visits, and develop treatment strategies that enables a transition to primary care. ResultsInterview and workshop data described a complex challenge due to the interaction of underlying pathophysiologies and the subsequent need for multiple care givers that hindered care continuity. The HND center partly met this challenge by coordinating care through multiple interprofessional and interdisciplinary shared decision-making interfaces. The large patient datasets were difficult to operationalize in daily practice due to data entry and retrieval issues. Predictive analytics was seen as a potentially effective approach to support decision-making, calculate risks, and improve resource utilization, especially in the context of complex chronic care, and the HND center a good place for pilot testing and development. Simplicity of visual interfaces, a better understanding of the algorithms by the health care professionals, and the need to address professional concerns, were identified as key factors to increase adoption and facilitate implementation. ConclusionsThe HND center serves as a comprehensive integrated practice unit that integrates different medical disciplinary perspectives in a person-centered care process to address the needs of patients with multiple complex comorbidities. Therefore, piloting predictive technologies at the same time with a high potential for improving care represents an extreme, demanding, and complex case. The study findings show that health care professionals’ involvement in the design of predictive technologies right from the outset can facilitate the implementation and adoption of such technologies, as well as enhance their predictive effectiveness and performance. Simplicity in the design of predictive technologies and better understanding of the concept and interpretation of the algorithms may result in implementation of predictive technologies in health care. Institutional efforts are needed to enhance collaboration among the health care professionals and IT professionals for effective development, implementation, and adoption of predictive analytics in health care.

Pragmatic co-design methodology: a tale of university and retirement village friendship

ABSTRACT Co-authored by academic staff and older adult community members, this paper reports on an incidental and pragmatic co-design model grounded in a round table friendship-informed approach. Interdisciplinary academics met with residents of a proximate retirement community, sharing open discussions with no agenda, including improving engagement between the two communities. The ensuing co-designed programme of outreach activities was of myriad mutual benefits: the retirement community benefited through opportunities for meaningful engagement via inter-generational knowledge-sharing, social connection, and access to expertise and equipment, whilst the University benefited across Learning and Teaching, Research, Engagement, and Commercialisation sectors. This pragmatic co-design approach described resulted in equitable contributions to knowledge generation, exchange, and translation in an interdirectional way. We argue that future research can adopt such an approach, exhibiting potential across all forms of community engaged research.

Predicting turbulent wake flow of marine hydrokinetic turbine arrays in large-scale waterways via physics-enhanced convolutional neural networks

We present a physics-enhanced convolutional neural network (PECNN) algorithm for reconstructing the mean flow and turbulence statistics in the wake of marine hydrokinetic (MHK) turbine arrays installed in large-scale meandering rivers. The algorithm embeds the mass and momentum conservation equations into the loss function of the PECNN algorithm to improve the physical realism of the reconstructed flow fields. The PECNN is trained using large eddy simulation (LES) results of the wake flow of a single row of turbines in a virtual meandering river. Subsequently, the trained PECNN is applied to predict the wake flow of MHK turbines with arrangements and positionings different than those considered during the training process. The PECNN predictions are validated using the results of separately performed LES. The results show that the PECNN algorithm can accurately predict the wake flow of MHK turbine farms at a small fraction of the cost of LES. The PECNN can improve the accuracy by around 1% and reduce the physical constraint indices by around 50% compared to the CNN without physical constraints. This work underscores the potential of PECNN to develop reduced-order models for control co-design and optimization of MHK turbine arrays in natural riverine environments.

NCI-Delirium Model: Co-caring to decrease the incidence of delirium among hospitalized older adults.

Delirium negatively impacts the health and wellbeing of older adults and their family carers and contributes to unnecessary high healthcare costs, estimated at $8.8 billion per year in Australia. Improvements to clinical practice are urgently needed, particularly now, as the COVID-19 pandemic is placing an enormous burden on our hospitals. 
 Innovative strategies that support partnerships with family carers have been reported as key to improved patient outcomes and satisfaction with care, particularly for older adults unable to participate in their own care. This is because carers have intimate knowledge of a family member’s cognitive state to identify early subtle changes others might not. Carers also provide valuable reassurance and familiarity to the older adults during their treatment and can orient them to place and time. 
 Founded on our clinical observations, informed by a scoping review of the literature (in press) and co-designed with carers, consumers, clinicians and policy analysts, we developed a new model of delirium care: NCI-Delirium. NCI-Delirium is a validated, scalable, low risk model that values the lived experience of older adults and carers. NCI-Delirium supports the integration of carers as partners in the care of the older adult from admission into the acute care setting. To support the integration of carers as partners, they are offered a web-based Delirium Toolkit that contains: an education package to build awareness and skill development (e.g., delirium risk factors, therapeutic and preventive strategies and non-pharmacological interventions to manage the reorientation of the hospitalised older adult); a 7-item psychometrically tested screening tool designed for carers to identify delirium symptoms and people at risk of delirium; access to support resources (e.g., counselling, social prescriptions, peer-support); and a co-designed discharge plan with the health team. 
 Preliminary results suggest that NCI-Delirium improves health service delirium outcomes. Carer involvement in this research, and the introduction of their perspectives, has elevated carers’ key relationships with clinicians. Our co-designed solution to support the integration of carers as partners in delirium management has improved carers’ caregiving burden, psychological wellbeing and knowledge of delirium. This translatable co-designed model of care provides the much needed rich and robust clinical, implementation and economic evidence, to address the risk factors associated with the prevalence of delirium in hospitalised older adults. It is anticipated that the model will transform how we integrate carers as partners in care to improve clinical practice, patient and carer experiences; and reduce caregiving burden.
 Globally, the identification and management of risk for delirium is imperative. Delirium is a potentially life-threatening condition, and not well detected in the acute or community care setting. If carers are integrated and supported as partners in care, the capacity to identify symptoms and support the diagnosis of delirium should increase, potentially reducing functional decline, transition to residential aged care facilities and mortality rates. The next steps are to evaluate this co-designed web-based delirium model of care for use by carers in the community and residential aged care setting.

Supporting Youth Mental Health through Co-designing a Virtual Reality Experience: A Recipe-Based Co-design Model

Supporting Youth Mental Health through Co-designing a Virtual Reality Experience: A Recipe-Based Co-design Model

A model of programmatic co-design with teachers: five factors for success

ABSTRACT This paper summarises the co-design model utilised throughout 2020–2022 by WeatherBlur, a community-based citizen science project. Project leaders and teachers working in classrooms across multiple states collaborated to develop iterative instructional practices for classroom implementation and professional development to support teachers’ use of the program. Participants received necessary support and training to facilitate their ongoing success as the project evolved and grew. External evaluators tracked the planning group’s co-design process, collecting data on the research-practitioner partnership and the ways their input impacted the project’s development over time. During the final year of the project, the planning group reflected upon their work and identified five criteria that emerged as successful elements of this co-design process. 1. Creating a culture of trust, 2. Time and patience, 3. Foundational knowledge and deconstruction for understanding, 4. Mutually beneficial collaboration, and 5. Commitment to engagement and flexibility. We present a full explanation of these five criteria, including how the WeatherBlur team developed and nurtured the associated behaviours and strategies. This set of takeaways is applicable to many contexts, and this paper provides insight for future co-design models seeking to replicate a development process that utilises collective resources and input from a range of collaborators.

P57: The ENGAGED study: dementia prevention co-design for people living with depression

Background:People living with depression are at increased risk of poor health outcomes, including dementia. Interventions to reduce dementia risk (dementia risk reduction (DRR)), include physical activity, diet and vascular health interventions. These can also benefit depressive symptoms and broader health, making DRR an important part of holistic mental health care for depression. However, enabling engagement and adherence, and embedding interventions in mental health clinician practice are ongoing challenges that limit the impact of interventions and implementation in clinical practice. Improved intervention tailoring and new approaches to intervention design and implementation are urgently needed. Co-design approaches have been shown to improve engagement and the impact of complex interventions in diverse fields, but have not previously been used in DRR.Objective:The ENGAGED study will examine DRR intervention needs specifically for people living with depression, then co-design a tailored DRR intervention for use in mental health clinical settings.Methods:The study will adapt a co-design model for mental health settings that emphasizes lived-expertise, and incorporate processes and evidence from behavioral science. Participants will include middle-aged and older people living with depression, and mental health clinicians.Semi-structured interviews with both participant groups will examine unmet intervention needs. Illuminated shared experiences and themes will be explored further through focus group discussions to develop consensus intervention priorities. They will also be analyzed to produce a contextualized model of relevant behavior change. Participants and researchers will then work together to co-design intervention components and refine prototypes. Finally, mixed methods survey will evaluate the co- design process and participant experiences.Results:This study will provide two key outputs to enhance future intervention tailoring and engagement: 1.1) a pragmatic blueprint for DRR intervention with people experiencing depression across diverse mental health clinical settings, ready for evaluation and implementation2.2) a model of DRR behavior change that is specified to this population.Evaluation findings will support methods development for applying co-design to cognitive and mental health research.Conclusion:This research addresses the need for new approaches to tailored, integrated mental, physical and cognitive healthcare for people living with depression that emphasize stakeholder expertise and engagement to facilitate holistic support.

Co-Creating the Future

Establishing a new learning design team at an offshore Australian institution in Vietnam midst the COVID-19 pandemic presented unique challenges. Lingering dissatisfaction with emergency remote teaching which primarily involved moving face to face teaching to online webinars (Turnbull, Chugh, & Luck, 2021) and limited exposure to intentional blended approaches (Maheshwari 2021; Le, Allen, & Johnson, 2022; Pham, Lai, & Nguyen, 2021) within the traditional, teacher-centered educational landscape of Vietnam (Pham & Ho, 2020; Yao & Collins, 2019) made this an extremely challenging task. This pecha-kucha documents our experiences establishing a learning design team and implementing a blended learning approach within this challenging context. Facing the challenge of generating interest and changing practice, we began in 2021, with one newly recruited learning designer and three early adopter faculty by using an iterative co-design model to support a participatory, collaborative approach to enhancing the overall learning experience (Huber & Jacka 2022; Wilson, Huber, & Bryant, 2021). This approach allowed us to support faculty professional development, establish design patterns, implement new asynchronous, interactive, social tools, and build knowledge about blended and online approaches, moving faculty away from the existing teacher dependent model (Pham, Lai, & Nguyen, 2021) with LMS as repository (Pham & Ho, 2020; Washington, 2019) to designing active, purposeful learning sequences connecting asynchronous and synchronous learning. These three initial courses were used to showcase our approach to senior stakeholders and secure buy in. Within one year, as positive word of mouth spread, demand for our services grew exponentially, to over 70 blended courses. As a direct result of this popularity, meeting each school's needs required tailoring support to scale up as well as expanding our team from 1 to 8 members. However, limited local expertise created hurdles amidst exponential demand, needing extensive on-the-job training and creative resourcing (Heggart & Dickson-Deane, 2022). While early generic workshops designed to address scale generated interest, they lacked practical relevance. Developing tailored support offerings addressed the specific needs of schools and programs and facilitated meeting the increased demand. Our ongoing codesign relationships with academics were crucial for moving academics to a more student-centered blended model with students taking more ownership of learning (Davis & Fill, 2007). As a complement and key focal point, we created a multipurpose Canvas site showcasing our design principles, tools, and sample modules from exemplar courses. This self-paced resource engaged stakeholders on their own terms, sparking interest while concurrently educating new learning designers and academics. We leveraged the site for showcase sessions, consultations, and events, updating it regularly to highlight approaches and design principles identified by the team as requiring extra support and attention. Through codesign relationships, exemplars showcasing value and tailored support, the learning design team successfully created awareness and enthusiasm to drive institutional change (McInnes, Aitchison, & Sloot, 2020, Taylor & Newton, 2013) toward an active, learner-centered blended approach. In this presentation, we will share specific strategies, tools, and lessons learned that equipped our team to foster stakeholder buy-in and scale up effectively. By documenting critical experiences and insights from our journey establishing awareness amidst obstacles, we aim to inspire innovative solutions so that others may successfully implement learner-centered pedagogies at their institutions under challenging conditions.

Co-design Model for Neuromorphic Technology Development in Rolling Element Bearing Condition Monitoring

This paper presents an end-to-end condition monitoring co-design model, from vibration measurement to anomaly detection, where conventional signal processing principles are combined with neuromorphic sensing and computing concepts to enable investigations of the potential improvements offered by brain-like information processing technologies.
 The use of machine learning in condition monitoring became increasingly popular for intelligent fault diagnosis in the last decade, taking advantage of the rapid developments in deep learning.
 However, the high computational cost of training and using deep neural networks prevents the use of such solutions for analysing the bulk of data generated by the resource constrained edge devices, i.e., the condition monitoring sensor systems, as only a minor fraction of data can be transmitted to the cloud or edge servers for analysis.
 There is an untapped potential to process this data and thereby improve intelligent fault diagnosis models using event-triggered sensing, spiking neural networks, and neuromorphic processors that substantially can improve the energy efficiency and capacity of embedded machine learning condition monitoring solutions.
 The proposed co-design model is evaluated on two use-cases involving rolling element bearing failures, one based on a labelled laboratory environment dataset, and one based on a wind turbine drivetrain bearing failure representing a real-world scenario with stochastic changes of machine state and unknown labels of the bearing condition.
 By adjusting co-design parameters, the resulting hybrid conventional/neuromorphic model show a comparable accuracy in detection performance for the laboratory dataset compared to the state-of-the-art reported in the literature.
 Similarly, for the wind turbine drivetrain dataset a bearing fault detection time comparable to that in previous work is obtained.
 This shows the successful implementation of a hybrid conventional/neuromorphic co-design model for condition monitoring applications, offering novel opportunities to investigate performance trade-offs and efficiency improvements enabled by neuromorphic technologies.

Psychosocial literacy at work: The role of digital data

Abstract The burden caused by poor psychosocial working environments on the working population, organizations, societies, and economies are a major challenge to occupational health, and fair work. A key enabler for accelerating the promotion of healthy and safe workplaces is the enhancement of psychosocial health literacy at work, to support not only workers and organizations but also communities and countries to understand, recognize and take effective actions to protect and promote their own psychosocial health and sustainability. Digitalization, on the other hand has been an enabler for knowledge creation and added value to information. The present work proposes a methodology that combines digital big data on psychosocial health of the Portuguese working population (PWP), allied with quantitative and qualitive approaches to the design of psychosocial literacy at work tailored interventions. In the promotion of psychosocial safe working environments collaborative co-design models are often recognized has effective because the process undertakes meaningful engagement with workers, enlarged community, health and safety professionals and decision makers, to uncover specific wisdom and ensure tailored psychosocial work literacy interventions. Each organization is unique and undertakes its own “personality”, so individualized interventions for dealing with the organization individual psychosocial profile are the most effective way to design such interventions. The digital data from the PWP are allied with a qualitative tailored approach admitting results maximization by using digital big data and algorithm calculation for several values and cluster identification incorporating individual and organizational specificities, using the data from the Portuguese Observatory on Occupational Factors (Popsy@Work). Its intended to raise awareness on the need to democratize the access to psychosocial health at work. Key messages • Digital big data on psychosocial health monitoring, reporting and foresight, allows the promotion of robust metrics and reference values for the Portuguese working population. • Psychosocial literacy at work is potentiated by collaborative co-design models – aligning digital big data and qualitative individualized approaches.

Out of time: (Re)working disabled graduate employability

As interest in disability employment increases across the world following the COVID-19 pandemic, understanding the employability of disabled graduates becomes an imperative for governments, universities and employers alike. This article investigates employability through the lens of the lived experience of disabled graduates, with one author (Alexandra) serving as a case study. Alexandra’s experience in higher education has been defined by living in crip time, a unique disabled experience of time as non-linear. Alexandra’s story describes how surviving within institutions which operate on normative understandings of time as linear, chronological, and inextricably tied to productivity has caused harm to disabled students. Disabled students are made to feel as though they are ‘falling behind time,’ ‘wasting time,’ and ‘losing time,’ resulting in a struggle to ‘catch up time,’ which impacts upon their wellbeing, confidence, and their sense of self. This struggle disadvantages disabled students from spending time building their ‘employability skills’ throughout their degree. As disabled students complete their studies and seek graduate employment, they come into further contact with industry who further compound harm through placement experiences and the graduate hiring process by not accommodating for crip time. This case study poses conventional mentoring programmes as a site in which disabled students such as Alexandra face barriers to engagement. We argue for a co-designed model of accessible, non-hierarchical peer mentoring, where crip time is accommodated and supported. Such accessible mentoring may serve as an effective intervention and an opportunity for disabled students to develop essential employability skills.

Process and outputs from a community codesign workshop on reducing impact of heat exposure on pregnant and postpartum women and newborns in Kilifi, Kenya.

Ambient heat exposure is increasing due to climate change and is known to affect the health of pregnant and postpartum women, and their newborns. Evidence for the effectiveness of interventions to prevent heat health outcomes in east Africa is limited. Codesigning and integrating local-indigenous and conventional knowledge is essential to develop effective adaptation to climate change. Following qualitative research on heat impacts in a community in Kilifi, Kenya, we conducted a two-day codesign workshop to inform a set of interventions to reduce the impact of heat exposure on maternal and neonatal health. Participants were drawn from a diverse group of purposively selected influencers, implementers, policy makers, service providers and community members. The key domains of focus for the discussion were: behavioral practices, health facilities and health system factors, home environment, water scarcity, and education and awareness. Following the discussions and group reflections, data was transcribed, coded and emerging intervention priorities ranked based on the likelihood of success, cost effectiveness, implementation feasibility, and sustainability. Twenty one participants participated in the codesign discussions. Accessibility to water supplies, social behavior-change campaigns, and education were ranked as the top three most sustainable and effective interventions with the highest likelihood of success. Prior planning and contextualizing local set-up, cross-cultural and religious practices and budget considerations are important in increasing the chances of a successful outcome in codesign. Codesign of interventions on heat exposure with diverse groups of participants is feasible to identify and prioritize adaptation interventions. The codesign workshop was used as an opportunity to build capacity among facilitators and participants as well as to explore interventions to address the impact of heat exposure on pregnant and postpartum women, and newborns. We successfully used the codesign model in co-creating contextualized socio-culturally acceptable interventions to reduce the risk of heat on maternal and neonatal health in the context of climate change. Our interventions can be replicated in other similar areas of Africa and serve as a model for co-designing heat-health adaptation.