Psychological distress among Japanese high school students during the COVID-19 pandemic: An energy landscape analysis

The stay-at-home orders, lockdowns, and states of emergency of the Coronavirus Infectious Disease emerged in 2019 (COVID-19) pandemic have affected the mental health of school-aged children. Previous reports of psychological distress in adolescents during the pandemic have been mixed, however, with some reports showing increases in psychological distress and others suggesting decreases. To accurately assess the impact of the pandemic, we need to be able to compare psychological assessments longitudinally, both before and during the pandemic. However, current statistical methods have limitations for reconstructing the complex trajectory of psychological states as captured by short-item questionnaires.

In this study, we analyzed monthly Kessler 6-item Psychological Distress Scale (K6) questionnaire responses collected from 16- to 18-year-old high school students participating in the population-neuroscience Tokyo TEEN Cohort (pn-TTC) in Japan (1,278 responses from 84 participants). Participants included 42 males and 42 females. The pn-TTC is a population-based longitudinal study conducted in Tokyo, Japan that follows children to investigate their developmental and mental health trajectories. In addition to conventional statistical approaches that summarize multiple questionnaire items into a composite score, we applied "energy landscape analysis," a method derived from statistical physics that models multivariate psychological states as a dynamic system of interactions among K6 questionnaire items, to visualize longitudinal changes in psychological distress before and during the COVID-19 pandemic (July 2019 to September 2021). Here, we define the depressive and healthy states as configurations in which all six K6 items are above or below each participant's individual mean, respectively. Before the pandemic, the healthy state occurred 11.0 times as frequently as the depressive state. In contrast, during the pandemic, the relative frequency of the healthy state increased to 18.2, 18.5, and 15.0 times that of the depressive state, respectively. The evolving energy landscape revealed an association between the pandemic period and a lower likelihood of being in a depressive state. We also identified two groups of students with different K6 dynamics and energy landscapes. The first group consisted of 61 participants whose total K6 score was relatively low (less than 5) and stable over time, and the second group consisted of 23 participants whose total K6 score was higher (with most being higher than 5) and less stable. The latter group showed a greater change in cortical thickness in the caudal part of the middle frontal gyrus (cMFG) (t-statistic = -2.36, p-value = 0.019, q-value = 0.048) and the temporal pole (TP) (t = 3.08, p = 0.0023, q = 0.012), as measured by magnetic resonance imaging, in the direction of accelerated adolescent brain development. Because all participants lived in Tokyo, generalizability remains limited, and as the association between psychological states and brain development is descriptive, future studies in diverse cohorts are needed to examine causality.

By revealing associations between the COVID-19 pandemic and lower levels of psychological distress and healthier mental health states, our work demonstrates the potential of using dynamical systems theory, such as the energy landscape analysis, to interpret health and disease metrics in psychology and psychiatry. This approach may improve mental health surveillance for the next pandemic.