Efficacy and Threat Language in PFAS Messaging

Rachel Hutchins et al.

Risk Analysis2026https://doi.org/10.1111/risa.70239article
AJG 4
Weight
0.50

What the paper says

As more Americans become aware of the threat of per- and polyfluoroalkyl substances (PFAS) in drinking water, they seek information using internet searches. Little is known, however, about the content of the websites produced by those searches or how well such content aligns with risk communication best practices. Guided by the Extended Parallel Processing Model and its two primary components, threat and efficacy, we analyze the top websites produced by Google searches relating to PFAS and water. We utilized a mixed-methods approach, with both qualitative content analysis and computational linguistic analysis, to examine how threat and efficacy are conveyed and how these portrayals differ by the type of message source. Our results show that news media sources and research sources are more likely to emphasize threat severity and individual susceptibility as well as to use negative emotion and anxious language, particularly in comparison with local government sites or water utility boards. News media was also more likely to provide efficacy information than other sources, but the overall emphasis on efficacy was low. Our results highlight the difference between established best practices and reality, offering recommendations for communicators across all source types to improve their PFAS communication and better aid the public.

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https://doi.org/https://doi.org/10.1111/risa.70239

Or copy a formatted citation

@article{rachel2026,
  title        = {{Efficacy and Threat Language in PFAS Messaging}},
  author       = {Rachel Hutchins et al.},
  journal      = {Risk Analysis},
  year         = {2026},
  doi          = {https://doi.org/https://doi.org/10.1111/risa.70239},
}

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Efficacy and Threat Language in PFAS Messaging

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Evidence weight

0.50

Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40

F · citation impact0.50 × 0.4 = 0.20
M · momentum0.50 × 0.15 = 0.07
V · venue signal0.50 × 0.05 = 0.03
R · text relevance †0.50 × 0.4 = 0.20

† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.