Improving Student Wellbeing: Evidence From a Mixed Effects Design and Comparison to Normative Data

BackgroundThe wellbeing of university students is deteriorating, highlighting a critical role for institutions to better support student wellbeing.ObjectiveThe goal of this work is to determine whether a final-year undergraduate wellbeing science module, inspired by recent theoretical developments, improved wellbeing during the COVID-19 pandemic.MethodParticipants (N = 128) completed a brief online questionnaire including the Warwick-Edinburgh Mental Well-being Scale across baseline and follow-up assessments. Analysis involved 2 group (intervention, control) ? 2 time (baseline T1, follow-up T2) mixed-effects analysis of variance (ANOVA) and one-sample t-tests to compare the intervention group with population-based norms for adults aged 16?75+.ResultsA significant interaction effect was observed, reflecting an increase in wellbeing in the intervention group in T2 relative to T1. Comparisons with published norms, further highlighted the beneficial impact of the module.ConclusionEncouraging connection to self, others and nature has beneficial impacts on wellbeing, consistent with a modern science of wellbeing.Teaching ImplicationsStudents learn the latest wellbeing theory, spanning the individual to the planet, and engage with opportunities to improve wellbeing, broadly defined. Teaching materials are made freely available for instructors wishing to develop a similar module or adapt materials for other purposes.

Use of Multiple Low Cost Carbon Dioxide Sensors to Measure Exhaled Breath Distribution with Face Mask Type and Wearing Behaviour.

The use of cloth face coverings and face masks has become widespread in light of the COVID-19 pandemic. This paper presents a method of using low cost wirelessly connected carbon dioxide (CO2) sensors to measure the effects of properly and improperly worn face masks on the concentration distribution of exhaled breath around the face. Four types of face masks are used in two indoor environment scenarios. CO2 as a proxy for exhaled breath is being measured with the Sensirion SCD30 CO2 sensor, and data are being transferred wirelessly to a base station. The exhaled CO2 is measured in four directions at various distances from the head of the subject, and interpolated to create spatial heat maps of CO2 concentration. Statistical analysis using the Friedman's analysis of variance (ANOVA) test is carried out to determine the validity of the null hypotheses (i.e., distribution of the CO2 is same) between different experiment conditions. Results suggest CO2 concentrations vary little with the type of mask used; however, improper use of the face mask results in statistically different CO2 spatial distribution of concentration. The use of low cost sensors with a visual interpolation tool could provide an effective method of demonstrating the importance of proper mask wearing to the public.

Protectors of Wellbeing During the COVID-19 Pandemic: Key Roles for Gratitude and Tragic Optimism in a UK-Based Cohort.

The COVID-19 pandemic has presented a global threat to physical and mental health worldwide. Research has highlighted adverse impacts of COVID-19 on wellbeing but has yet to offer insights as to how wellbeing may be protected. Inspired by developments in wellbeing science and guided by our own theoretical framework (the GENIAL model), we examined the role of various potentially protective factors in a sample of 138 participants from the United Kingdom. Protective factors included physical activity (i.e., a health behaviour that helps to build psychological wellbeing), tragic optimism (optimism in the face of tragedy), gratitude (a prosocial emotion), social support (the perception or experience of being loved, cared for, and valued by others), and nature connectedness (physical and psychological connection to nature). Initial analysis involved the application of one-sample t-tests, which confirmed that wellbeing (measured by the Warwick-Edinburgh Mental Well-being scale) in the current sample (N = 138; M = 46.08, SD = 9.22) was significantly lower compared to previous samples (d = -0.36 and d = -0.41). Protective factors were observed to account for up to 50% of variance in wellbeing in a hierarchical linear regression that controlled for a range of sociostructural factors including age, gender, and subjective social status, which impact on wellbeing but lie beyond individual control. Gratitude and tragic optimism emerged as significant contributors to the model. Our results identify key psychological attributes that may be harnessed through various positive psychology strategies to mitigate the adverse impacts of hardship and suffering, consistent with an existential positive psychology of suffering.