What, Me Worry? The Role of Affect in Information Seeking and Avoidance
Abstract
Guided by the risk information-seeking and processing model, this study examines positive and negative affect separately in their influence on information-seeking intentions and avoidance through structural equation analyses. The highlight is that information avoidance seems to be driven by positive affect, while information seeking seems to be more heavily influenced by negative affect. Another interesting finding is that informational subjective norms are positively related to both seeking and avoidance, which suggests that one’s social environment has the potential to strongly influence the way he or she handles climate change information. Implications for theory and practice are discussed.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
Additional research has found support for PRISM as an acceptable model for predicting information seeking intentions.
“Additional research has found support for PRISM to be an acceptable model for predicting information seeking intentions [26-28].”
From A Cross-Cultural Comparison of an Extended Planned Risk Information Seeking Model on Mental Health Among College Students: Cross-Sectional Study (2020) · cites this paper as [26]
Cites
Schwarz, N., & Clore, G. L. (1983) · Journal of Personality and Social Psychology · doi:10.1037/0022-3514.45.3.513 · Cited by 4,952 · see citing works
Communication and Uncertainty Management
Brashers, D. E. (2001) · Journal of Communication · doi:10.1111/j.1460-2466.2001.tb02892.x · Cited by 1,407 · see citing works
Griffin, R. J., Dunwoody, S., & Neuwirth, K. (1999) · Environmental Research · doi:10.1006/enrs.1998.3940 · Cited by 1,187 · see citing works
PRISM: A Planned Risk Information Seeking Model
Kahlor, L. (2010) · Health Communication · doi:10.1080/10410231003775172 · Cited by 531 · see citing works
Self-citation
Flagged first, then by citations
Cited by
Sorted by citations
Anxiety, worry, and grief in a time of environmental and climate crisis: a narrative review
Ojala, M., Cunsolo, A., Ogunbode, C. A., & Middleton, J. (2021) · Annual Review of Environment and Resources · doi:10.1146/annurev-environ-012220-022716 · Cited by 670 · see citing works
Kim, H. K., Ahn, J., Atkinson, L., & Kahlor, L. A. (2020) · Science Communication · doi:10.1177/1075547020959670 · Cited by 313 · see citing works
Self-citationNegative online news articles are shared more to social media
Watson, J., van der Linden, S., Watson, M., & Stillwell, D. (2024) · Scientific Reports · doi:10.1038/s41598-024-71263-z · Cited by 70 · see citing works
Niu, Z., Willoughby, J. F., Mei, J., Li, S., & Hu, P. (2020) · Journal of Medical Internet Research · doi:10.2196/15817 · Cited by 21 · see citing works
- Authors
- Yang, Z. J., & Kahlor, L.
- Affiliations
- University at Buffalo, The State University of New York, USA
- The University of Texas at Austin, USA
- Venue
- Science Communication
- Publisher
- SAGE Publications
- Published
- 2012-05-24
- Volume
- 35
- Issue
- 2
- Pages
- 189-212
- ISSN
- 0164-0259 (ISSN-L)
- 1075-5470
- 1552-8545
- OpenAlex
- W2112433418
- Cited by
- 346
- References
- 4
- Citations by year
- 2026: 40 · 2025: 36 · 2024: 40 · 2023: 38 · 2022: 43 · 2021: 28 · 2020: 34 · 2019: 17 · 2018: 23 · 2017: 10 · 2016: 10 · 2015: 8 · 2014: 13 · 2013: 5
- FWCI
- 25.62
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Science Communication (publishedVersion)
- Topics
- Social Sciences › Sociology and Political Science › Climate Change Communication and Perception
- Social Sciences › Sociology and Political Science › Risk Perception and Management
- Social Sciences › Communication › Public Relations and Crisis Communication
- Keywords
- affect, information seeking, information avoidance, positive affect, negative affect, risk information seeking and processing model, climate change information, risk communication
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
