Eco-anxiety: Towards a medical model and the new framework of ecolalgia.

INTRODUCTION: In the context of global warming, new terms emerged in the global media and in the psychology field to embody the negative feelings which come along with climate change such as 'eco-anxiety' or 'solastalgia'. The pathological character of these emotions is denied although medical opinion is often required for helping people to handle them. Also, no proper medical framework in the field exists to study and care for these patients. METHODS: In this narrative review, we aim to (1) analyse the concept of eco-anxiety by focusing on its history and developed concepts, (2) summarize the different scales built to assess eco-anxiety and (3) propose a new medical framework. RESULTS: We came out with a framework based on the transformation of a physiological adaptative behaviour the 'eco-distress'. It is composed of three dimensions: eco-anger, eco-grief and eco-worry, it is not debilitating in daily life and promotes coping strategies such as management of negative emotions and pro-environmental behaviours (PEB). It can transform itself into a pathological state, the 'ecolalgia', composed of two core dimensions: eco-anxiety and eco-depression, leading to functional impairment and decrease in PEB. If ecolalgia maintains over 15 days, we propose to consider it as a full psychiatric disorder needing medical advice. CONCLUSION: This new framework enables a novel approach that is necessary for the improved management of mental health issues related to climate change.

Factors associated with insomnia symptoms: A cross-sectional study during a Covid-19 fully restrictive lockdown.

Insomnia is the most frequent sleep disorder and a public health concern that increased during the Covid 19 pandemic. Fully restrictive lockdowns during Covid are interesting periods to examine the impact of environmental and behavioural changes on the emergence of insomnia symptoms. In this cross-sectional study we aimed to (1) determine the main factors associated with insomnia symptoms during a Covid-19 fully restrictive lockdown examining the associated daily life alterations and (2) create a predictive model of insomnia symptoms. We used the data drawn from the "Covid-RythmE" study that reached volunteers from the general French population through an online survey during the last 2 weeks of the 2 month full lockdown. Associations with insomnia symptoms were tested and significant associations were entered in a Backward Stepwise Logistic Regression (BSLR) to assess the best combination to classify individuals with or without insomnia symptoms. From the 1624 participants, 50.64% suffered from mild to severe insomnia symptoms as assessed by the ISI. The best combination for explaining insomnia symptoms with 74.26% of accuracy included: age (OR = 1.15), females (OR = 1.26), smaller home sizes (OR = 0.77), environmental noises (OR = 1.59), anxiety symptoms (OR = 1.24), depressive symptoms (OR = 1.15), regularity of sleep-wake schedules (OR = 1.25), exposure to screen during the morning (OR = 1.13), and LED light during the evening (OR = 1.17). Thus, lifestyle schedule and exposure to natural synchronizers such as light, are primordial in considering in insomnia physiopathology, prevention and treatment, as well as the associated mental health status.