First responders, such as paramedics and firefighters, encounter duty-related traumatic exposures, which can lead to post-traumatic stress (PTS). Although social support protects against PTS, we know little about how first responders’ families, spouses/partners, friends, and care-partners (i.e., ‘trusted others’) provide social support. This narrative review explores support behaviors, coping strategies, and resources trusted others use to support first responders. A structured literature search yielded 24 articles. We used House’s (1981) conceptual framework to inform our analysis. We identified three main themes: providing support, finding support, and support needs. Additionally, we describe trusted others’ self-reported preparedness, coping strategies, and barriers to providing social support. We found that trusted others provided different types of support: (a) emotional (fostering a safe space, giving autonomy over recovery, facilitating coping mechanisms, prioritizing first responders’ emotional needs); (b) instrumental (prioritizing first responders’ practical needs, handling household tasks, supporting recovery); (c) appraisal (active monitoring, verbal reassurance, positive reframing), and (d) informational (seeking informal learning). In their role, trusted others sought formal (organizational) and informal (peer and personal) support and resources, alongside intrapersonal and interpersonal coping strategies. Identified barriers include inadequate communication skills, maladaptive coping, and disempowering beliefs. Thus, we offer practical, treatment, and social support recommendations.

Three key challenges to a whole-system approach to process improvement in health systems are the complexity of socio-technical activity, the capacity to change purposefully, and the consequent capacity to proactively manage and govern the system. The literature on healthcare improvement demonstrates the persistence of these problems. In this project, the Access-Risk-Knowledge (ARK) Platform, which supports the implementation of improvement projects, was deployed across three healthcare organisations to address risk management for the prevention and control of healthcare-associated infections (HCAIs). In each organisation, quality and safety experts initiated an ARK project and participated in a follow-up survey and focus group. The platform was then evaluated against a set of fifteen needs related to complex system transformation. While the results highlighted concerns about the platform’s usability, feedback was generally positive regarding its effectiveness and potential value in supporting HCAI risk management. The ARK Platform addresses the majority of identified needs for system transformation; other needs were validated in the trial or are undergoing development. This trial provided a starting point for a knowledge-based solution to enhance organisational governance and develop shared knowledge through a Community of Practice that will contribute to sustaining and generalising that change.

This paper proposes a framework for developing a trustworthy artificial intelligence (AI) supported knowledge management system (KMS) by integrating existing approaches to trustworthy AI, trust in data, and trust in organisations. We argue that improvement in three core dimensions (data governance, validation of evidence, and reciprocal obligation to act) will lead to the development of trust in the three domains of the data, the AI technology, and the organisation. The framework was informed by a case study implementing the Access-Risk-Knowledge (ARK) platform for mindful risk governance across three collaborating healthcare organisations. Subsequently, the framework was applied within each organisation with the aim of measuring trust to this point and generating objectives for future ARK platform development. The resulting discussion of ARK and the framework has implications for the development of KMSs, the development of trustworthy AI, and the management of risk and change in complex socio-technical systems.