According to a survey run between April and May 2020 in the United Kingdom and Ireland, a majority of audiences would feel comfortable going to an event again if a limit on the number of attendees was imposed and they didn't have to stand in long queues. Roughly ** percent also claimed they would feel safe attending if seats were spaced at least * meters apart, while nearly ** percent would like hand sanitizer to be provided.

This data is the result of a study carried out in March and April of 2020 in response to the novel coronavirus pandemic. The purpose of the study was to evaluate the suitability of common fabrics for homemade face masks. This was conducted in light of the severe PPE (Personal Protective Equipment) shortage caused by the pandemic.

This data was collected using a setup described by Irwin M. Hutton in his 2016 book Handbook of Nonwoven Filter Media, 2nd edition. This testing method and filtration calculation study is consistent with those used in similar studies on particle filtration. For this study, a 1" diameter tubing apparatus was adapted to give access to two P-Trak Ultrafine Particle Counters. Air was pulled through the apparatus at a rate of approximately 16.5 meters per second. Upstream concentrations represent number of ultrafine particles present in the air before it passes through the filter medium. Downstream concentrations represent number of ultrafine particles present after the air has passed through the filter medium. Readings were taken simultaneous 1.5” before and after the filter medium holder. Each data point represents a 10-second average of ultrafine particle concentrations present in passing air. Filtration efficiency was calculated according to Irwin M. Hutten’s formula. For further information on the setup and filtration efficiency (FE) calculations, refer to Chapter 3 of Handbook of Nonwoven Filter Media, 2nd edition, written by Irwin M. Hutton and published by Buttterworth and Heinemann in 2016: https://doi.org/10.1016/B978-0-08-098301-1.00003-4

Music is a tool used in daily life in order to mitigate negative and enhance positive emotions. Listeners may orientate their engagement with music around its ability to facilitate particular emotional responses and to subsequently regulate mood. Existing scales have aimed to gauge both individual coping orientations in response to stress, as well as individual use of music for the purposes of mood regulation. This study utilised pre-validated scales through an online survey (N = 233) in order to measure whether music’s use in mood regulation is influenced by coping orientations and/or demographic variables in response to the lockdown measures imposed in the United Kingdom, as a consequence of the COVID-19 pandemic. Whilst factor analyses show that the existing theoretical structure of the COPE model has indicated a poor fit for clustered coping orientations, a subsequent five-factor structure was determined for coping orientations in response to lockdown. Analyses include observations that positive reframing and active coping (Positive Outlook) were strong predictors of music use in mood regulation amongst listener’s coping strategies, as was Substance Use. Higher Age indicated having a negative effect on music’s use in mood regulation, whilst factors such as gender were not seen to be significant in relation to the use of music in mood regulation within this context. These results provide insight into how individuals have engaged with music orientated coping strategies in response to a unique stressor.

Demographics of survey respondents; *obtained from Welsh Government data online [32].

Univariable (model 3) and multivariable (model 4) logistic regression models of self-reported school-based mitigation measures (survey) and individual level (school staff) self-reported cold symptoms (survey).

The continued impact of COVID-19 on adolescent mental health, educational attainment and future prospects is of great concern. The aim of this study was to capture the experiences of adolescents as the pandemic unfolds and longer-term societal and economic consequences emerge. Adolescents may be of particular risk for adverse effects due to COVID-19 as this was a period of increased risk for developing psychopathology (Fairchild 2011, Paus et al 2008), as well as a crucial time for establishing personal identity/independence. During this period, peer relationships are especially important (Albarello et al 2018, Hay and Ashman 2003, Steinberg & Morris 2001). Hence, the normal developmental processes of adolescence are likely to be disrupted by the COVID-19 pandemic. Nonetheless, there are individual differences in responses to adversity so that not all individuals exposed to the same stressors will experience adverse effects or impaired mental health (Cicchetti 2010) and some exhibit better-than-expected responses to adversity, a phenomenon known as 'resilience' (Galatzer-Levy et al 2018, Masten 2011, Yule et al 2019).

This study has been designed to explore which factors (e.g., gender, ethnicity, socioeconomic status, family function, decision-making abilities) determine the impact of the pandemic on young adolescents. The basis for this work was established just over a year ago when an online survey was conducted to examine the impact of Covid-19 on young people aged 13-24 (n = 2002, stratified by age, ethnicity and deprivation index) as part of the COVID-19 Research Consortium Study (C19PRC, https://osf.io/v2zur/wiki/home/).

The study's findings revealed unique challenges faced by younger adolescents in terms of the impact of the pandemic on their mental health and highlighted the importance of key factors that are not currently being addressed, e.g., young people's social and psychological adjustment and difficulty in enacting health behaviour (Levita et al 2020a, Levita et al 2020b). Due to a lack of resources, this study did not include follow-ups or further exploration of the lived experience of the pandemic from young people themselves. Consequently, the objective was to build on this work and enrich the self-report data to more accurately profile the mental health and well-being of adolescents, by following a representative sub-sample aged 13-16 from the original cohort one year on.

To that end, the research encompassed

(1) conducted qualitative individual personal interviews (virtually) with participants. This is a more personal form of research that helps to better explore and understand participants' opinions, behaviour, and experiences and has been missing from research on the Impact of COVID-19 on young adolescents (e.g., Ares et al 2021, Copeland et al 2021, Hawes et al 2021).

(2) Mental health, well-being, and resilience indices was gathered from an online survey.

(3) Using short smartphone tasks, decision-making indices, that can provide an accurate way (less prone to bias) to gauge how mood affects the way these young people make decisions about risk.

These tasks have been shown by the team to predict anxiety symptoms and real-time COVID-19 health behaviour (including social distancing adherence) in adults (Lloyd et al 2020). In the rapidly changing context of the COVID-19 pandemic, this work will help policy makers understand, from young people's perspective, which groups of young people need support to aid their well-being; when they need support and what kind of support they would like, from evidence-based research.

Univariable (model 5) and multivariable (model 6) logistic regression models of self-reported school-based mitigation measures (survey) and individual level (school staff) moderate/severe anxiety symptoms (survey).

Distribution of individual school staff responses to mitigation survey items and school-level response agreement (see S3 Appendix).