Aims: Increased mental health problems during the COVID-19 pandemic have become a major concern among young adults. Our aim was to understand which COVID-19-related questions predicted mental well-being during the outbreak. Methods: Two cross-sectional datasets were used. The primary dataset was collected in May 2020 ( n = 1001), during the initial COVID-19 outbreak, and the secondary in April 2019 ( n = 10866), before the pandemic. Mental well-being was assessed with the Short Warwick–Edinburgh Mental Well-Being Scale. Relationships between mental well-being and COVID-19-related questions were investigated with lasso regression. As an exploratory analysis, two-way ANOVAs were used to compare mental well-being before and during the outbreak. Results: Higher levels of mental well-being were associated with lower levels of academic stress and COVID-19-related worry, along with a higher satisfaction with the procedures and information provided by the higher education institutions and the government. COVID-19-related symptoms and infections did not have an impact on students’ mental well-being during the outbreak. Small to moderate effect sizes across the time points were detected, indicating an overall decrease in mental well-being across age and gender during the outbreak. Conclusions: COVID-19 had an impact on higher education students’ mental well-being. Higher education institutes may play a crucial role in protecting their students’ well-being during uncertain times.

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Background The aim of this study was to examine physical activity and sedentary behaviours during Western Australia’s COVID-19 lockdown and their association with mental well-being. Methods Participants completed activity related questions approximately two months after a three-month lockdown (which formed part of a larger cross-sectional study from August to October 2020) as part of a 25-minute questionnaire adapted from the Western Australia Health and Well-being Surveillance system. Open-ended questions explored key issues relating to physical activity behaviours. Results During the lockdown period, 463 participants (female, n = 347; 75.3%) reported lower number of active days (W = 4.47 p < .001), higher non-work-related screen hours per week (W = 11.8 p < .001), and higher levels of sitting time (χ2=28.4 p < .001). Post lockdown body mass index was higher (U = 3.0 p = .003), with obese individuals reporting the highest non-work-related screen hours per week (Wald χ2= 8.9 p = .012). Inverse associations were found for mental well-being where higher lockdown scores of Kessler-10 (p = .011), Dass-21 anxiety (p = .027) and Dass-21 depression (p = .011) were associated with lower physical activity levels. A key qualitative message from participants was wanting to know how to stay healthy during lockdown. Conclusions Lockdown was associated with lower physical activity, higher non-work-related screen time and more sitting time compared to post lockdown which also reported higher body mass index. Lower levels of mental well-being were associated with lower physical activity levels during lockdown. Given the known positive affect of physical activity on mental well-being and obesity, and the detrimental associations shown in this study, a key public health message should be considered in an attempt to maintain healthy activity behaviours in future lockdowns and similar emergency situations to promote and maintain positive well-being. Furthermore, consideration should be given to the isolation of a community due to infectious disease outbreaks and to recognise the important role physical activity plays in maintaining weight and supporting good mental health.

IntroductionThis study explored the behavioral profiles of residing Western Australians during a COVID-19 lockdown period and transitions in behavior post-lockdown.MethodsA total of 313 participants (76% female, age: M = 50.1, SD = 15.7 years) completed behavioral and mental health questionnaire items ~2 months after a 3-month COVID-19 lockdown in October 2020, using a retrospective recall to assess their experience during the lockdown period. Latent transition analysis (LTA) was used to identify behavioral profiles and transitions. Indicators were identified by assessing during–post-lockdown group differences (Kruskal–Wallis, chi-square tests) and profiles described using qualitative open-ended questions.ResultsSignificant indicators included changes in physical activity, leisure screen time, alcohol intake, psychological distress, and loneliness, but not fast food consumption. The significant indicators were used to form LTA models. The five latent class model showed the best model fit (Log-likelihood = −1301.66, AIC = 426.12, BIC = 609.68). Approximately one in four participants reported a change in their behavior profiles after the lockdown ceased. Key differences between the profiles were age, household income, education, resilience, sense of control, existing mental health issues, and social relations. Washing hands and social distancing were the most recalled and effective health campaigns across the classes, with health campaigns encompassing physical activity/alcohol consumption, or domestic violence having the least attention.DiscussionOverall, while most participants recovered relatively well after the lockdown period, LTA did identify subgroups such as those who were inactive and lonely experienced more difficulties than other groups, and engagement with public health campaigns differed. The results provide important insights for future public health campaigns on how these campaigns might be diversified to effectively target more people and particular groups to maximize engagement for maintaining people's mental health with additional focus on physical activity, alcohol consumption, and domestic violence.

Brain–computer interfaces (BCIs) can be used in real-time fMRI neurofeedback (rtfMRI NF) investigations to provide feedback on brain activity to enable voluntary regulation of the blood-oxygen-level dependent (BOLD) signal from localized brain regions. However, the temporal pattern of successful self-regulation is dynamic and complex. In particular, the general linear model (GLM) assumes fixed temporal model functions and misses other dynamics. We propose a novel data-driven analyses approach for rtfMRI NF using intersubject covariance (ISC) analysis. The potential of ISC was examined in a reanalysis of data from 21 healthy individuals and nine patients with post-traumatic stress-disorder (PTSD) performing up-regulation of the anterior cingulate cortex (ACC). ISC in the PTSD group differed from healthy controls in a network including the right inferior frontal gyrus (IFG). In both cohorts, ISC decreased throughout the experiment indicating the development of individual regulation strategies. ISC analyses are a promising approach to reveal novel information on the mechanisms involved in voluntary self-regulation of brain signals and thus extend the results from GLM-based methods. ISC enables a novel set of research questions that can guide future neurofeedback and neuroimaging investigations.