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Abstract. Like many other mountainous countries, Norway has experienced a rapid
increase in both recreational winter activities and fatalities in avalanche
terrain during the past few decades: during the decade 2008–2017,
64 recreational avalanche fatalities were recorded in Norway. This is a
106 % increase from that of the previous decade. In 2013, Norway therefore
launched the National Avalanche Warning Service (NAWS), which provides
avalanche warnings to transport and preparedness authorities and to the
public. Previous studies suggest that avalanche warnings are used extensively
in trip and preparedness planning and have a relatively strong influence on
the decisions people make in order to reduce risk. However, no evaluation
concerning how efficiently the warnings are communicated and understood has
been done to date in Norway. Avalanche warnings communicate complex natural
phenomena with a variable complexity and level of uncertainty about both the
future and the present. In order to manage avalanche risk successfully, it is
fundamental that the warning message can be understood and translated into
practice by a wide range of different user groups. Users with little or no
avalanche competence may need simple information to decide when to stay away
from avalanche terrain, while professional users may need advanced technical
details in order to make their decisions. To evaluate how different modes of
communication are understood, and how efficiently the informational content
is communicated, we designed and implemented a web-based user survey. The
modes of presentation were based on the Varsom.no 2017 version (Varsom.no
being the national portal for natural hazard warnings in Norway). We first
used a panel of 110 experts from NAWS to answer the survey, and used their
answers to establish the indented message of the avalanche warning. We
thereafter received responses from 264 users and compared their answers to
those of the NAWS experts for the different modes of communication. We
developed a method, the comprehension effectiveness score, to test the
comprehension. Our empirical analyses suggest that most users find the
warning service to be useful and well suited to their needs. However, the
effectiveness of a warnings seems to be influenced by the competency of the
user and the complexity of the scenarios. We discuss the findings and make
recommendations on how to improve communication of avalanche warnings.

Background: The Introduction of mobile health (mHealth) devices to health intervention studies challenges us as researchers to adapt how we analyse the impact of these technologies. For interventions involving chronic illness self-management, we must consider changes in behaviour in addition to changes in health. Fortunately, these mHealth technologies can record participants' interactions via usage-logs during research interventions. Objective: The objective of this paper is to demonstrate the potential of analysing mHealth usage-logs by presenting an in-depth analysis as a preliminary study for using behavioural theories to contextualize the user-recorded results of mHealth intervention studies. We use the logs collected by persons with type 2 diabetes during a randomized controlled trial (RCT) as a use-case. Methods: The Few Touch Application was tested in a year-long intervention, which allowed participants to register and review their blood glucose, diet and physical activity, goals, and access general disease information. Usage-logs, i.e. logged interactions with the mHealth devices, were collected from participants (n = 101) in the intervention groups. HbA1c was collected (baseline, 4- and 12-months). Usage logs were categorized into registrations or navigations. Results: There were n = 29 non-mHealth users, n = 11 short-term users and n = 61 long-term users. Non-mHealth users increased (+0.33%) while Long-term users reduced their HbA1c (-0.86%), which was significantly different (P = .021). Long-term users significantly decreased their usage over the year (P < .001). K-means clustering revealed two clusters: one dominated by diet/exercise interactions (n = 16), and one dominated by BG interactions and navigations in general (n = 40). The only significant difference between these two clusters was that the first cluster spent more time on the goals functionalities than the second (P < .001). Conclusion: By comparing participants based upon their usage-logs, we were able to discern differences in HbA1c as well as usage patterns. This approach demonstrates the potential of analysing usage-logs to better understand how participants engage during mHealth intervention studies. ; The EU's ICT Policy Support Programme as part of the Competitiveness and Innovation Framework Programme(http://ec.europa.eu/cip/) (No. 250487)and The Research Councilof Norway (norges forskningsråd, https://www. forskningsradet.no/no/Forsiden/1173185591033) (No. 196364)funded the study designand data collection and analysis through the REgioNs of Europe WorkINg toGether for HEALTH (RENEWING HEALTH) project (https://cordis. europa.eu/project/rcn/191719_en.html), led by Lis Ribu and EirikÅrsand.The Research Council of Norway (norges forskningsråd, https://www. forskningsradet.no/no/Forsiden/1173185591033) funded the preparation of the manuscript and decision to publish through the "Full Flow of Health Data Between Patientsand Health Care Systems" project (https://ehealthresearch.no/en/projects/ fullflow) (grant number 247974/O70), led by Eirik Årsand.The publication charges for this article have been funded by a grant from the publication fund of UiT The Arctic University of Norway (https://uit.no/ub/forskningsstotte/art?p_ document_id=449104)(No. 551011),led by Meghan Bradway.The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. Norges forskningsråd 247974 ; publishedVersion

The COVID-19 pandemic forced millions of people to drastically change their social life habits as governments employed harsh restrictions to reduce the spread of the virus. Although beneficial to physical health, the perception of physical distancing and related restrictions could impact mental health. In a pre-registered online survey, we assessed how effective a range of restrictions were perceived, how severely they affected daily life, general distress and paranoia during the early phase of the outbreak in Brazil, Colombia, Germany, Israel, Norway and USA. Most of our over 2000 respondents rated the restrictions as effective. School closings were perceived as having the strongest effect on daily life. Participants who believed their country reacted too mildly perceived the risk of contracting SARS-CoV-2 to be higher, were more worried and expressed reduced beliefs in the ability to control the outbreak. Relatedly, dissatisfaction with governmental reactions corresponded with increased distress levels. Together, we found that satisfaction with one's governmental reactions and fear appraisal play an important role in assessing the efficacy of restrictions during the pandemic and their related psychological outcomes. These findings inform policy-makers on the psychological factors that strengthen resilience and foster the well-being of citizens in times of global crisis.