Additional file 1 of The effect of intolerance of uncertainty on anxiety and depression, and their symptom networks, during the COVID-19 pandemic
Creators: name: Andrews, Jack L.
name: Li, Meiwei
name: Minihan, Savannah
name: Songco, Annabel
name: Fox, Elaine
name: Ladouceur, Cecile D.
name: Mewton, Louise
name: Moulds, Michelle
name: Pfeifer, Jennifer H.
name: Van Harmelen, Anne-Laura
name: Schweizer, Susanne
Publisher: name: figshare
Year: 2024
Subjects: subject: Medicine
subject: Neuroscience
subject: Chemical Sciences not elsewhere classified
subject: Science Policy
subject: Sociology
subject: FOS: Sociology
subject: Cancer
subject: Mental Health
subject: Computational Biology

description: Additional file 1: Table S1. Mean and standard deviations of depression (PHQ-8), Anxiety (GAD-7) and Intolerance of Uncertainty (IUS-12) at each time point. Table S2. Estimates for models predicting depression when controlling for age, gender and covid risk, respectively. Table S3. Estimates for models predicting anxiety when controlling for age, gender and covid risk, respectively. Table S4. Results from the Network Comparison Test, assessing differences in network structure invariance and global strength invariance. Fig. S1. Network diagram of depressive and anxiety symptoms for the full sample at T1. Table S5. Node predictability at T1 for the full sample. Fig. S2. The relative scores for strength and closeness centrality are plotted for each node within the network at T1 for the full sample. Table S6. Results from the Network Comparison Test, assessing differences in network structure invariance and global strength invariance, across time and by country. Table S7. Post-hoc edge weight differences conducted on the edges of a network model comprised of intolerance of uncertainty (sum score of IUS-12) and depression (PHQ-8) and anxiety (GAD-7) symptoms, between T1 and T3 from adults in the UK and USA. Table S8. Stability Co-efficients for betweenness, closeness and strength centrality, computed on a network model comprised of intolerance of uncertainty (sum score of IUS-12) and depression (PHQ-8) and anxiety (GAD-7) symptoms, across time and by country. Fig. S3. Stability plots for betweenness, closeness and strength centrality by sample and time point. Table S9. Differences in strength centrality of each node, computed on a network model comprised of intolerance of uncertainty (sum score of IUS-12) and depression (PHQ-8) and anxiety (GAD-7) symptoms, from the full sample across time. Table S10. Node predictability of each symptom, computed on a network model comprised of intolerance of uncertainty (sum score of IUS-12) and depression (PHQ-8) and anxiety (GAD-7) symptoms, from the full sample across time. Table S11. Edge weight differences between intolerance of uncertainty and each other symptom node in the network, computed on a network model comprised of intolerance of uncertainty (sum score of IUS-12) and depression (PHQ-8) and anxiety (GAD-7) symptoms, from the full sample at T1 (between May 5, 2020, and September 30, 2020). Table S12. Edge weight differences between intolerance of uncertainty and each other symptom node in the network, computed on a network model comprised of intolerance of uncertainty (sum score of IUS-12) and depression (PHQ-8) and anxiety (GAD-7) symptoms, from the full sample at T2 (between August 5, 2020, and January 29, 2021). Table S13. Edge weight differences between intolerance of uncertainty and each other symptom node in the network, computed on a network model comprised of intolerance of uncertainty (sum score of IUS-12) and depression (PHQ-8) and anxiety (GAD-7) symptoms, from the full sample at T3 (between November 5, 2020, and April 9, 2021). Table S15. Model estimates from a model predicting felling afraid (GAD 7) with an interaction between intolerance of uncertainty and survey completion date (time). Fig. S4. The moderating effect of survey completion date (time) on the relationship between intolerance of uncertainty and feeling afraid (GAD 7).