TY - JOUR
T1 - Network analysis of pandemic fatigue symptoms in samples from five South American countries
AU - Caycho-Rodríguez, Tomás
AU - Torales, Julio
AU - Ventura-León, José
AU - Barrios, Iván
AU - Waisman-Campos, Marcela
AU - Terrazas-Landivar, Alexandra
AU - Viola, Laura
AU - Vilca, Lindsey W.
AU - Muñoz-del-Carpio-Toia, Agueda
N1 - Publisher Copyright:
© The Author(s) 2024.
PY - 2024/5
Y1 - 2024/5
N2 - Background: Pandemic fatigue generates low motivation or the ability to comply with protective behaviors to mitigate the spread of COVID-19. Aims: This study aimed to analyze the symptoms of pandemic fatigue through network analysis in individuals from five South American countries. Method: A total of 1,444 individuals from Argentina, Bolivia, Paraguay, Peru, and Uruguay participated and were evaluated using the Pandemic Fatigue Scale. The networks were estimated using the ggmModSelect estimation method and a polychoric correlation matrix was used. Stability assessment of the five networks was performed using the nonparametric resampling method based on the case bootstrap type. For the estimation of network centrality, a metric based on node strength was used, whereas network comparison was performed using a permutation-based approach. Results: The results showed that the relationships between pandemic fatigue symptoms were strongest in the demotivation dimension. Variability in the centrality of pandemic fatigue symptoms was observed among participating countries. Finally, symptom networks were invariant and almost identical across participating countries. Conclusions: This study is the first to provide information on how pandemic fatigue symptoms were related during the COVID-19 pandemic.
AB - Background: Pandemic fatigue generates low motivation or the ability to comply with protective behaviors to mitigate the spread of COVID-19. Aims: This study aimed to analyze the symptoms of pandemic fatigue through network analysis in individuals from five South American countries. Method: A total of 1,444 individuals from Argentina, Bolivia, Paraguay, Peru, and Uruguay participated and were evaluated using the Pandemic Fatigue Scale. The networks were estimated using the ggmModSelect estimation method and a polychoric correlation matrix was used. Stability assessment of the five networks was performed using the nonparametric resampling method based on the case bootstrap type. For the estimation of network centrality, a metric based on node strength was used, whereas network comparison was performed using a permutation-based approach. Results: The results showed that the relationships between pandemic fatigue symptoms were strongest in the demotivation dimension. Variability in the centrality of pandemic fatigue symptoms was observed among participating countries. Finally, symptom networks were invariant and almost identical across participating countries. Conclusions: This study is the first to provide information on how pandemic fatigue symptoms were related during the COVID-19 pandemic.
KW - COVID-19
KW - South America
KW - networks
KW - pandemic fatigue
UR - http://www.scopus.com/inward/record.url?scp=85183854905&partnerID=8YFLogxK
U2 - 10.1177/00207640231223430
DO - 10.1177/00207640231223430
M3 - Article
AN - SCOPUS:85183854905
SN - 0020-7640
VL - 70
SP - 601
EP - 614
JO - International Journal of Social Psychiatry
JF - International Journal of Social Psychiatry
IS - 3
ER -