World Beliefs Moderate the Effects of Trauma and Severe Illness on Emotional Distress

World beliefs appear to buffer individuals from emotional distress following severe illness or trauma. Further, the specific content of these beliefs, as well as their valence, appears important for emotional resilience.

Authors

Institutions

Publication Details

Journal
Journal of Personality
Published
2025-11-12
DOI
https://doi.org/10.1111/jopy.70031
Citations
1
Primary Topic
Psychosomatic Disorders and Their Treatments
Type
article
Field-Weighted Citation Impact
1.47
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

World Beliefs Moderate the Effects of Trauma and Severe Illness on Emotional Distress

Adrienne Wood, Nicholas Kerry, Shigehiro Oishi, Shelly Tsang et al.
1 citations
Journal of Personality
Psychosomatic Disorders and Their Treatments
1.47
article

World Beliefs Moderate the Effects of Trauma and Severe Illness on Emotional Distress

Adrienne Wood, Nicholas Kerry, Shigehiro Oishi, Shelly Tsang, Jeremy D. W. Clifton, Janna Hämpke, K. C. White, Kyle Barrantine
article en
1 citations

Abstract

World beliefs appear to buffer individuals from emotional distress following severe illness or trauma. Further, the specific content of these beliefs, as well as their valence, appears important for emotional resilience.

Journal of Personality
University of Vienna (AT), University of Chicago (US), University of Virginia (US), University of Pennsylvania (US), Ludwig-Maximilians-Universität München (DE)
Openalex Percentile: Top 14%
Psychosomatic Disorders and Their Treatments
1.47
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.