Sleep and mental health in the Belgian population during the COVID-19 Pandemic

The COVID-19 pandemic, deemed a global health emergency between 2020 and 2023, had a significant
impact worldwide not only on physical health and mortality, with 3.4 million deaths reported by the
WHO, but also on mental health due to the anxiogenic, changing, and novel context in which society
was evolving. This thesis aimed to investigate mental health and sleep by means of network analysis.
To do so, four studies were carried out, focusing on different cohorts, namely first responders within a
hospital population during the first two lockdowns during the COVID-19 pandemic, as well as the
general population and finally, shortly after the last confinement an adolescent and young adult
populations. Anxiety and depressive symptoms, sleep habits as well as insomnia symptomatology were
measured by means of the Generalized Anxiety Disorder 7-item, Patient Health Questionnaire 9-item,
and the Insomnia Severity Index. Next to symptom intensities, we systematically investigated the
network structure of these symptoms using undirected (Ising and Gaussian Graphical Models (GGMs))
and directed (Bayesian Directed Acyclic Graphs (DAGs)) network analysis in order to reveal mutual and
directional dependencies.
First, our findings indicate that frontline workers reported significantly higher anxiety, depression, and
insomnia symptom intensities compared to other hospital staff members during the first and fourth
waves. However, the disparity in the intensity of these complaints slightly diminished during the fourth
wave, occurring more than a year after the first. Secondly, our findings reveal that during the first
lockdown, the general population experienced a significant increase in complaints of insomnia, anxiety,
and depression, which intensified even further during the second lockdown in Belgium suggesting
prolonged impacts on sleep and mental health due to the ongoing pandemic. Finally, our results also
demonstrated that sleep habits among the adolescent and young adult population changed during the
lockdown compared to the easing down of the containment measures in early 2022. Among them,
participants reported advanced bedtime and wake time, as well as a subjectively longer total sleep
time, compared to the lockdown periods and regardless of chronotype. This population also showed a
slight increase in depressive and anxious symptoms during the lockdowns, while insomnia complaints
remained similar.
Network analyses revealed that the network topology (i.e., the relational structure between
symptoms) in healthcare workers was not influenced by exposure (i.e. working as a frontline hospital
worker or not). Moreover, anxiety seemed to play a pivotal role during the two periods investigated,
due to the presence of several anxiety symptoms possessing the highest centrality indices and their
locations situated upstream of the DAGs, suggesting that other symptoms are directionally dependent
of anxiety and may contribute to the maintenance of other mental health issues. Regarding the general
population, it is also noted that this network topology was not significantly influenced by the
lockdowns. Furthermore, our analyses reveal that here diurnal symptoms of insomnia have the highest
centrality indices and are located at the top of the DAG (whereas they are located towards the end of
the cascade in healthcare workers). Finally, the network analysis of the adolescent and young adult
population demonstrated that an increase in mental fatigue during the lockdown was among the most
central changes in the model, and also appeared as the parent node of the DAG, indicating that the
presence of this change implied more the presence of other changes connected to this mental fatigue,
rather than the reverse.
In conclusion, this thesis has firstly allowed us to highlight a greater intensity of symptoms of anxiety,
depression, and insomnia in frontline workers compared to other hospital professions, but also an
2
intensity of these same symptoms for the general population that was exacerbated by the two
lockdowns imposed in Belgium, and especially during the second. The adolescent and young adult
population, on the other hand, is characterized by insomnia complaints that were not intensified during
the lockdowns, but rather by changing sleep habits during these periods. Secondly, the various network
analyses conducted during this thesis highlight the phenomenon that the variables contributing to the
intensification of symptoms are not necessarily the same as those that change their interrelational
structure. From a therapeutic viewpoint, this underscores an interesting phenomenon of robustness,
or resilience, of the relationships present between an individual's complaints, even as an external event
intensifies or, conversely, mitigates them. This underlines the importance of personalized therapeutic
care that should target for some more the external factor influencing intensity, while for others it will
focus more on the internal relationships between the different components of the complaints network.
Future research could also look into the evaluation of such personalized care, by collecting longitudinal
and personalized data, to later integrate them into temporal network analyses, precisely adapted to
causal inferences that would be crucial for the evaluation of this kind of idiographic care.