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Frontiers in psychology, 2021-06, Vol.12, p.663627-663627
2021
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Autor(en) / Beteiligte
Titel
A Novel Network Approach to Capture Cognition and Affect: COVID-19 Experiences in Canada and Germany
Ist Teil von
  • Frontiers in psychology, 2021-06, Vol.12, p.663627-663627
Ort / Verlag
Switzerland: Frontiers Media S.A
Erscheinungsjahr
2021
Quelle
Free E-Journal (出版社公開部分のみ)
Beschreibungen/Notizen
  • We tested a novel method for studying human experience (thoughts and affect). We utilized Cognitive-Affective Maps (CAMs)-an approach to visually represent thoughts and their affective connotations as networks of concepts that individuals associate with a given event. Using an innovative software tool, we recruited a comparative sample of ( = 93) Canadians and ( = 100) Germans to draw a CAM of their experience (events, thoughts, feelings) with the Covid-19 pandemic. We treated these CAM networks as a series of directed graphs and examined the extent to which their structural properties (latent and emotional) are predictive for the perceived coronavirus threat (PCT). Across multiple models, we found consistent and significant relationships between these network variables and the PCT in both the Canadian and German sample. Our results provide unique insights into individuals' thinking and perceptions of the viral outbreak. Our results also demonstrate that a network analysis of CAMs' properties is a promising method to study the relationship between human thought and affective connotation. We suggest that CAMs can bridge several gaps between qualitative and quantitative methods. Unlike when using quantitative tools (e.g., questionnaires), participants' answers are not restricted by response items as participants are free to incorporate any thoughts and feelings on the given topic. Furthermore, as compared to traditional qualitative measures, such as structured interviews, the CAM technique may better enable researchers to objectively assess and integrate the substance of a shared experience for large samples of participants.
Sprache
Englisch
Identifikatoren
ISSN: 1664-1078
eISSN: 1664-1078
DOI: 10.3389/fpsyg.2021.663627
Titel-ID: cdi_doaj_primary_oai_doaj_org_article_68ea17942ff740a9a3684a8179d2de4b

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