RESOUT

Burnout affects 40% of resident physicians. It is a public health and social problem, due to its high prevalence and negative impact on personal health, patient care and economic costs. Its consequences are both for professionals and patients, as it impairs drastically the foundations of medical care (more errors) and patient-doctor relationship (less empathy) (4). Its prevalence is higher among surgical residencies (1). About two thirds of affected residents do not recover without intervention; only one third seek help. When untreated, medical burnout is associated with increased rates of depression, suicidality and substance abuse and to augmented economic costs due to absenteeism, reduced clinical hours and rapid turnover of doctors (3). The highest residents’ risk comes from an interplay between their individual and contextual factors., in which personality traits play a central role (11). Medical schools and hospitals are challenging environments (5) and attract people with stress-prone personality traits, such as perfectionism (8), which increase the impact of the typical residency stressors, and thus, their risk of psychological distress. We have found that this maladaptive trait leads to depression, anxiety, fatigue (9,10) and burnout (11), namely in medicine students, by increasing levels of negative repetitive thinking (14). We have recently proved that both perfectionism and psychological distress/burnout are negatively correlated with mindfulness and self compassion, namely in medical students and residents (11). Our latest research on this topic highlight the potential long-term benefits of interventions aimed at increasing self-compassion on the mental health of medical students, particularly those with high levels of perfectionism (14). Before starting internship, young physicians with higher levels of burnout have lower mindfulness and self-compassion skills and a recent meta analysis has shown that mindfulness-based practices are effective in reducing physicians’ burnout and stress (21). Although promising, the effects have almost exclusively been measured by self-reports, except for a recent RCT that used self-report measures and cortisol secretion as a stress biomarker, to prove the efficacy of an adapted program considering residents' specific needs and focusing on integrating mindfulness into daily medical practice (22). The objectives of our proposal are to: develop the app RESOUT to collect and monitor psychometric and cognitive-emotional, behavioural, neuro psychological and neuro-physiological parameters with ecological momentary assessment methods (EMA; active and passive); to test the RESOUT effectiveness in reducing residents’ burnout and distress. The app will identify profiles based on automatically detected data (location, workload, heart-rate, sleep-wake rhythm, activity, mood, sociability and social connectivity) and self-reported levels of burnout, distress, perfectionism and self-reported levels of burnout, psychological distress, personality traits (perfectionism), emotional regulation strategies and empathy. Then, using Artificial Intelligence and Intelligent Personal Assistant Agents, it will deliver personalized digital materials, mainly focused on mindfulness and self-compassion strategies. The efficacy of mindfulness-type interventions for doctors’ burnout is compromised by their rigid and intense schedules. Digital alternatives are thus recommended, due to its higher accessibility, flexibility, personalization to users and effectiveness. We want to implement a RCT to test the app effectiveness not only with psychometric, biologic (hair cortisol) and EMA variables, but also through neuroimaging techniques, which is completely innovative; Residents with high burnout levels will be randomly assigned to the experimental group/EG or to one of the two control groups/CG (n=60 each): CG1-standard MBSR; CG2-waiting list. EG and CGs participants will use the RESOUT app in the assessment mode; only EG will also use the intervention mode. A subgroup of surgical residents with high levels (n=15), while using the app, will enter in a fMRI study including two neurocognitive tasks (clinical decision-making and empathy). By identifying the neuroimaging correlates of burnout, the effect of using the RESOUT app may be extended to the comparison of neural activation patterns and connectivity. Although the interest in using smartphone apps to reduce residents' stress is increasing, so far none have proposed to validate their effectiveness at a fundamental level. This will be the first study measuring simultaneously psychological, ecological emotional and behavioural, neuropsychological, neurophysiological parameters and neurofunctional variables related to burnout. Our proposal to develop and test a digital tool for physicians’ burnout using artificial intelligence technologies to personalize and tailor the intervention is also completely innovative.