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To ensure high-quality care, operationalize resilience and fill the knowledge gap regarding how to improve the prerequisites for resilient performance, it is necessary to understand how adaptive capacity unfolds in practice. The main aim of this research was to explain the escalation process of intensive care during the first wave of the pandemic from a microlevel perspective, including expressions of resilient performance, intervening conditions at the micro-meso-macrolevels and short- and long-term consequences. A secondary aim was to provide recommendations regarding how to optimize the prerequisites for resilient performance in intensive care. A grounded theory methodology was used. First-person stories from different healthcare professionals (n70) in two Swedish regions were analyzed using the constant comparative method. This resulted in a novel conceptual model (including 6 main categories and 24 subcategories), and 41 recommendations. The conclusion of these findings is that the escalation of intensive care can be conceptualized as a transition from threatening chaos to temporary order through a complex process of adaptation. To prepare for the future, the components of space, stuff, staff, system and science, with associated continuity plans, must be implemented, anchored and communicated to actors at all levels of the system.

ObjectiveType D personality, a joint tendency toward negative affectivity and social inhibition, has been linked to adverse events in patients with heart disease, although with inconsistent findings. Here, we apply an individual patient-data meta-analysis to data from 19 prospective cohort studies (N = 11,151) to investigate the prediction of adverse outcomes by type D personality in patients with acquired cardiovascular disease.MethodFor each outcome (all-cause mortality, cardiac mortality, myocardial infarction, coronary artery bypass grafting, percutaneous coronary intervention, major adverse cardiac event, any adverse event), we estimated type D's prognostic influence and the moderation by age, sex, and disease type.ResultsIn patients with cardiovascular disease, evidence for a type D effect in terms of the Bayes factor (BF) was strong for major adverse cardiac event (BF = 42.5; odds ratio [OR] = 1.14) and any adverse event (BF = 129.4; OR = 1.15). Evidence for the null hypothesis was found for all-cause mortality (BF = 45.9; OR = 1.03), cardiac mortality (BF = 23.7; OR = 0.99), and myocardial infarction (BF = 16.9; OR = 1.12), suggesting that type D had no effect on these outcomes. This evidence was similar in the subset of patients with coronary artery disease (CAD), but inconclusive for patients with heart failure (HF). Positive effects were found for negative affectivity on cardiac and all-cause mortality, with the latter being more pronounced in male than female patients.ConclusionAcross 19 prospective cohort studies, type D predicts adverse events in patients with CAD, whereas evidence in patients with HF was inconclusive. In both patients with CAD and HF, we found evidence for a null effect of type D on cardiac and all-cause mortality.

Health consequences have been reported among health-care workers (HCWs) exposed to COVID-19. Sweden chose to manage the pandemic with a lower and more equal long-lasting work strain and shorter periods of recovery than in other countries. Few studies have examined the health consequences among HCWs working in such conditions. This study compared the health consequences after the first wave of the COVID-19 pandemic between HCWs involved in the care of COVID-19 patients and other HCWs and between occupational groups working in COVID-19 care. Multinomial logistic regression and univariate general linear models were used to identify differences. The levels of depression, emotional and physical fatigue, sleep quality, and general health were measured 6 months after the onset of the pandemic in 3495 HCW employed in Sweden. HCWs directly involved in COVID-19 care reported significantly poorer sleep quality and higher scores on emotional and physical exhaustion than those not involved in such care. Health consequences did not differ significantly between different occupational groups involved in COVID-19 care except for specialist nurses/midwives. HCWs more frequently involved in COVID-19 care reported higher levels of emotional and physical fatigue and poorer sleep but less severe than those reported in more severely affected countries.

INTRODUCTION: Since early 2020, the COVID-19 pandemic has challenged societies and revealed the built-in fragility and dependencies in complex adaptive systems, such as healthcare. The pandemic has placed healthcare providers and systems under unprecedented amounts of strain with potential consequences that have not yet been fully elucidated. This multilevel project aims to explore resilient performance with the purpose of improving the understanding of how healthcare has adapted during the pandemic's rampage, the processes involved and the consequences on working conditions, ethics and patient safety. METHODS: An emerging explorative multilevel design based on grounded theory methodology is applied. Open and theoretical sampling is performed. Empirical data are gathered over time from written narratives and qualitative interviews with staff with different positions in healthcare organisations in two Swedish regions. The participants' first-person stories are complemented with data from the healthcare organisations' internal documents and national and international official documents. ANALYSIS: Experiences and expressions of resilient performance at different system levels and times, existing influencing risk and success factors at the microlevels, mesolevels and macrolevels and inter-relationships and consequences in different healthcare contexts, are explored using constant comparative analysis. Finally, the data are complemented with the current literature to develop a substantive theory of resilient performance during the pandemic. ETHICS AND DISSEMINATION: This project is ethically approved and recognises the ongoing strain on the healthcare system when gathering data. The ongoing pandemic provides unique possibilities to study system-wide adaptive capacity across different system levels and times, which can create an important basis for designing interventions focusing on preparedness to manage current and future challenges in healthcare. Feedback is provided