Skip to content
akaturk Academic measurement

Article detail · 2022

Genuine high-order interactions in brain networks and neurodegeneration

Journal

Neurobiology of Disease

ISSN 0969-9961

YÖKSİS OpenAlex Open access · gold SJR Q1 JCR Q1 Citations 50 Top 10% Percentile 98.6% FWCI 8.71
Year
2022
Type
article

Data source split

  • YÖKSİS YÖKSİS article record
  • YÖKSİS venue Neurobiology of Disease
  • Catalog match (ISSN) Neurobiology of Disease
  • OpenAlex OpenAlex enrichment (abstract, citations, topics)

Abstract

OpenAlex · English

Abstract At the beginning of 2020, COVID-19 became a global problem. Despite all the efforts to emphasize the relevance of preventive measures, not everyone adhered to them. Thus, learning more about the characteristics determining attitudinal and behavioral responses to the pandemic is crucial to improving future interventions. In this study, we applied machine learning on the multi-national data collected by the International Collaboration on the Social and Moral Psychology of COVID-19 (N = 51,404) to test the predictive efficacy of constructs from social, moral, cognitive, and personality psychology, as well as socio-demographic factors, in the attitudinal and behavioral responses to the pandemic. The results point to several valuable insights. Internalized moral identity provided the most consistent predictive contribution—individuals perceiving moral traits as central to their self-concept reported higher adherence to preventive measures. Similar was found for morality as cooperation, symbolized moral identity, self-control, open-mindedness, collective narcissism, while the inverse relationship was evident for the endorsement of conspiracy theories. However, we also found a non-negligible variability in the explained variance and predictive contributions with respect to macro-level factors such as the pandemic stage or cultural region. Overall, the results underscore the importance of morality-related and contextual factors in understanding adherence to public health recommendations during the pandemic.

Topics

Citations

OpenAlex cited_by_count. Not a WoS or Scopus citation count; those sources have no separate column here.

50 citations

OpenAlex cited_by_count (cache / database)

Authors

  1. AGUSTİN MARİANO IBANEZ İSTANBUL MEDİPOL ÜNİVERSİTESİ