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Patterns of Digital Media Engagement During Wartime and Their Associations With Stress, Resilience, and Well-Being:
Moti Zwilling1,2, Galit Klein1, Sharon Barak3
1Department of Economics and Business Administration, Ariel University, Ariel, Judea and Samaria Area, Israel.
Background:
During wartime, civilians rely on digital media for information, connection, and coping. However, engagement patterns may differ in their associations with stress, resilience, and well-being.
Objective:
This study aimed to characterize patterns of digital media engagement during wartime and examine their associations with stress, resilience, and well-being in a cross-sectional survey of Israeli adults.
Methods:
We conducted a cross-sectional web-based survey in Israel in early January 2024. Participants (N=512; age: range18-65, mean 37.54, SD 12.89 years; 241/512, 47.1% male) were recruited using nonprobability quota sampling. Well-being was measured using the 5-item World Health Organization Well-Being Index, stress using the 21-item Depression Anxiety Stress Scales stress subscale, and resilience using the 10-item Connor-Davidson Resilience Scale. Participants reported the extent to which their use of 10 digital media activities increased since the beginning of the war (5-point Likert scale). Analyses included 2-step cluster analysis, exploratory factor analysis (principal axis factoring with Promax rotation), and structural equation modeling path analysis.
Results:
Cluster analysis identified 2 engagement profiles: low engagement (126/512, 24.6%) and high engagement (386/512, 75.4%; silhouette coefficient=0.30). The high-engagement profile reported higher stress (median 2.39, 95% CI 2.31-2.47) than the low-engagement profile (median 2.01, 95% CI 1.87-2.15; P<.001). Exploratory factor analysis supported a 3-factor structure (active, passive, and institutional engagement), explaining 61.86% of the variance (Kaiser-Meyer-Olkin=0.77; Bartlett χ236=1007.6; P<.001). Structural equation modeling showed acceptable fit (χ21=1.5; P=.21; Comparative Fit Index=0.999; Tucker-Lewis Index=0.981; standardized root-mean-square residual=0.013; root-mean-square error of approximation=0.033). Resilience was negatively associated with stress (β=-0.24, 95% CI -0.34 to -0.14; P<.001) and positively associated with well-being (β=0.30, 95% CI 0.18-0.42; P<.001). Stress was positively associated with active (β=0.27, 95% CI 0.17-0.37; P<.001), passive (β=0.31, 95% CI 0.21-0.41; P<.001), and institutional engagement (β=0.16, 95% CI 0.06-0.26; P<.001). Active engagement was positively associated with well-being (β=0.12, 95% CI 0.04-0.20; P=.006), passive engagement showed a negative trend (β=-0.08, 95% CI -0.18 to 0.02; P=.08), and institutional engagement was not significantly associated with well-being (β=0.07, 95% CI -0.01 to 0.15; P=.11). The total indirect association between resilience and well-being through stress and engagement was significant (indirect effect=0.09, 95% bootstrap CI 0.05-0.13).
Conclusions:
Wartime digital media engagement clustered into distinct profiles and dimensions, each showing different associations with stress, resilience, and well-being. This study advances the field by empirically distinguishing active, passive, and institutional engagement, with the latter often overlooked in crisis-media research. The findings offer a more detailed framework for understanding how civilians navigate digital environments during an ongoing armed conflict and provide practical implications for psychosocial guidance and crisis communication, encouraging more intentional engagement and reducing excessive passive consumption. Causal inferences are limited by the cross-sectional design.
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