| Literature DB >> 35585793 |
Sonja Utz1,2, Franziska Gaiser, Lara N Wolfers1.
Abstract
During the COVID-19 pandemic, virologists gained a prominent role in traditional and social media in Germany; several participated in regular podcasts. Using a two-wave survey (n = 696/361 at Time 1/2), we explore which impact the strong media presence of virologists had on media users and what role parasocial phenomena (asymmetric interactions and relationships with virologists) played. People who favored a specific virologist scored higher on various cognitive, affective, and behavioral outcomes. Exposure to the virologist was related to these outcomes and parasocial phenomena turned out as an intervening variable between exposure and subjective and objective knowledge (time 1), solace, and behavioral engagement (both times). We did not, however, find effects over time when controlling for the time 1 values, which rather speak against more long-term media effects. A higher need for leadership also predicted the formation of parasocial phenomena. We discuss the theoretical implications for the role of parasocial phenomena in science communication via digital media.Entities:
Keywords: COVID-19; Podcasts; knowledge; parasocial phenomena; science communication
Mesh:
Year: 2022 PMID: 35585793 PMCID: PMC9386758 DOI: 10.1177/09636625221093194
Source DB: PubMed Journal: Public Underst Sci ISSN: 0963-6625
Figure 1.Conceptual model.
Figure 2.Procedure and questionnaires for (sub)samples.
Descriptives and intercorrelations: Wave 1.
|
| n | 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | 10 | 11 | 12 | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 Parasocial phenomena | 3.99 (1.34) | 380 | – | |||||||||||
| 2 Solace | 4.33 (1.36) | 380 | .48 | – | ||||||||||
| 3 Coping efficacy | 5.30 (1.20) | 695 | .08 | .09 | – | |||||||||
| 4 Individual efficacy | 5.93 (1.01) | 696 | .15 | .26 | .26 | – | ||||||||
| 5 Collective efficacy | 5.96 (0.99) | 696 | .08 | .21 | .22 | .74 | – | |||||||
| 6 Knowledge subjective | 5.17 (0.96) | 696 | .25 | .13 | .16 | .16 | .14 | – | ||||||
| 7 Knowledge objective | 3.10 (0.54) | 696 | .17 | .04 | −.05 | −.02 | −.03 | .16 | – | |||||
| 8 Preventive behavior | 4.58 (0.41) | 696 | .10 | .20 | .09 | .45 | .39 | .13 | −.03 | – | ||||
| 9 Behavioral engagement | 1.46 (0.86) | 371 | .36 | .22 | .04 | .07 | .06 | .19 | .14 | .03 | – | |||
| 10 Need for leadership | 4.26 (1.19) | 694 | .13 | .12 | .07 | .27 | .27 | .03 | .00 | .18 | .04 | – | ||
| 11 Frequency podcast | 7.47 (8.46) | 381 | .42 | .20 | −.01 | .04 | .03 | .19 | .08 | .08 | .18 | .01 | – | |
| 12 Exposure general | 1.99 (1.94) | 696 | .41 | .24 | .00 | .13 | .14 | .25 | .16 | .18 | .20 | .10 | .41 | – |
| 13 Number of channels | 2.59 (1.35) | 381 | .28 | .15 | .04 | .09 | .04 | .16 | .10 | .16 | .25 | .06 | .18 | .37 |
p < .05; **p < .01; ***p < .001.
Figure 3.Cross-sectional model at t1.
N = 355. χ2(467) = 671.55, p < .001; CFI = .95; RMSEA = .035; significant indirect effects: FP→SK β = 0.08, p = .018; EG→SK β = 0.05, p = .036; FP→OK β = 0.07, p = .037; EG→OK β = 0.05, p = .046; FP→SO β = 0.20, p < .001; NC→SO β = 0.08, p = .010; EG→SO β = 0.14, p < .001; FP→BE β = 0.18, p < .001; NC→BE β = 0.07, p = .019; EG→BE β = 0.12, p = .001. Insignificant paths, factor loadings and correlations are not shown to simplify the figure. For complete results see OSF.
Figure 4.Model across both waves.
N = 92, χ2(182) = 225.64, p = .015; CFI = .95; RMSEA = .051; no significant indirect effects over time. Insignificant paths for exposure to T2 variables, factor loadings and correlations are not shown to simplify the figure. For complete results see OSF.