Lockdown measures during the COVID-19 pandemic resulted in drastic disruptions of university students’ everyday life and study mode, such as marked reductions in face-to-face teaching activities. ...Previous research on student mental health during the pandemic found that prolonged campus relocation had negative effects on students’ mental well-being. However, these studies focussed on the
initial
lockdown period, or periods of
active
lockdown measures. This longitudinal study collected 456 observations of 23 undergraduate students in the Netherlands using ecological momentary assessment data on mental health related items (anxiety, stress, social context) during the first two weeks of on-campus teaching after prolonged lockdown measures. Using multi-level dynamic network modelling, we analysed the temporal and contemporaneous interplay of students’ mental health factors following the return to campus in September 2021. On average, students reported low to medium scores on stress and anxiety both before and after the assessment period. Results of network analyses showed that students experienced social unease in relation to accumulating difficulties at university and vice versa. Furthermore, there were clusters of different states of social unease next to clusters of stress, anger, loss of control, and feeling upset. Lastly, we found beneficial effects of self-efficacy on experiencing social comfort in university. We discuss implications and concrete examples of interventions in universities, such as the promotion of self-efficacy, providing guidance in structuring study load, as well as help with stress management.
Many people have flipped coins but few have stopped to ponder the statistical and physical intricacies of the process. In a preregistered study we collected \(350{,}757\) coin flips to test the ...counterintuitive prediction from a physics model of human coin tossing developed by Diaconis, Holmes, and Montgomery (DHM; 2007). The model asserts that when people flip an ordinary coin, it tends to land on the same side it started -- DHM estimated the probability of a same-side outcome to be about 51%. Our data lend strong support to this precise prediction: the coins landed on the same side more often than not, \(\text{Pr}(\text{same side}) = 0.508\), 95% credible interval (CI) \(0.506\), \(0.509\), \(\text{BF}_{\text{same-side bias}} = 2359\). Furthermore, the data revealed considerable between-people variation in the degree of this same-side bias. Our data also confirmed the generic prediction that when people flip an ordinary coin -- with the initial side-up randomly determined -- it is equally likely to land heads or tails: \(\text{Pr}(\text{heads}) = 0.500\), 95% CI \(0.498\), \(0.502\), \(\text{BF}_{\text{heads-tails bias}} = 0.182\). Furthermore, this lack of heads-tails bias does not appear to vary across coins. Additional exploratory analyses revealed that the within-people same-side bias decreased as more coins were flipped, an effect that is consistent with the possibility that practice makes people flip coins in a less wobbly fashion. Our data therefore provide strong evidence that when some (but not all) people flip a fair coin, it tends to land on the same side it started. Our data provide compelling statistical support for the DHM physics model of coin tossing.
