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This study explored the experiences of Irish emergency medical services (EMS) first responders during the first nationwide restrictions to curb the spread of COVID-19.

A systematic literature review (SLR) of research into healthcare workers' and first responders' experiences during the COVID-19 and 2003 SARS pandemics was performed. The SLR informed the content of an online questionnaire distributed via the Irish Pre-Hospital Emergency Care Council to 2,092 first responders on its live register. Data analysis used both descriptive and content analysis.

EMS first responders faced many challenges including PPE quality, training on its use, issues with decontamination facilities, and organisational effectiveness. Emotional challenges included the anxiety experienced, the impact on families, and ethical dilemmas confronted related to patient care. Positive findings also emerged, such as first responders' dedication to working through the pandemic, collegiality, and the community goodwill displayed.

While investigations of the impact of the COVID-19 pandemic on healthcare workers have been undertaken globally, studies focussing exclusively on the experiences of EMS first responders have been rare. This study addressed this knowledge gap, providing an insight into the challenges and successes experienced by first responders and identifying opportunities for learning that can be applied to future public health emergencies.

The introduction of quality management Internet of things (QM IoT) can help food supply chain members to enhance real-time visibility, quality, safety and efficiency of products and processes. Current literature indicates three main research gaps, including a lack of studies in QM IoT in the food supply chain, the vagueness of integrative adoption of new technology framework and deficient research covering both adoption attitude and intention in the same model. This study aims to propose an analysis model based on the technological–organizational–environmental (TOE) framework and reinforced by the collaborative structure to capture the importance of the supply chain network.

The partial least square-structural equation modeling (PLS-SEM) was applied to test the impacts of the adoption factors on QM IoT adoption attitude and intention among 197 respondents in food manufacturing in Thailand.

The results indicated that compatibility, trialability, adaptive capacity, innovative capability, executive support, value chain partner pressure, presence of service provider and information sharing significantly impacted the attitude toward QM IoT adoption, while adaptive capability, innovative capability and information sharing directly influenced the QM IoT adoption intention. Furthermore, the attitude toward QM IoT adoption positively impacted the QM IoT adoption intention.

This study contributed to academicians by proposing a more solid adoption framework for QM IoT area. In addition, the business practitioners could actively prepare themselves for the QM IoT adoption, whereas the service providers could provide better and suitable service.

This research contributes to the building of a more solid framework and indicates significant factors that impact the attitude toward QM IoT adoption and adoption intention.