Tweeting the Heat: An Analysis of the National Weather Service’s Approach to Extreme Heat Communication on Twitter

Michele K. Olson aCollege of Emergency Preparedness, Homeland Security and Cybersecurity, University at Albany, State University of New York, Albany, New York

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Jeannette Sutton aCollege of Emergency Preparedness, Homeland Security and Cybersecurity, University at Albany, State University of New York, Albany, New York

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Nicholas Waugh aCollege of Emergency Preparedness, Homeland Security and Cybersecurity, University at Albany, State University of New York, Albany, New York

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Abstract

Heat communication interventions are an essential way that public safety organizations can reduce extreme heat consequences for at-risk groups. Although the aim of these interventions is typically behavior change, these organizations commonly assume that providing information about heat risks, impacts, vulnerable populations, and protective actions will lead individuals to protect themselves. However, behavior change is a complex process whereby messages must be crafted in ways that increase their persuasive effects. To examine the extent to which key assumptions about behavior change are present in public safety organizations’ heat communication interventions, we examine 250 heat-related tweets sent by seven National Weather Service (NWS) weather forecast offices (WFOs) in 2021. We find that these NWS WFOs use technical language or “jargon” to communicate about heat risks and impacts. In addition, we find that information about vulnerable populations and protective actions is not presented in a way that conforms to theory on behavior change. Based on these results, we offer recommendations to increase the persuasiveness of NWS WFO communication interventions that encourage the public to protect themselves during extreme heat events.

Significance Statement

Heat is the leading cause of death among all weather-related hazards. How heat is communicated to the public can help mitigate heat-related morbidity and mortality. However, heat communication interventions are often developed with several embedded assumptions about behavior change that negatively impact their effectiveness. By examining how a key public safety organization communicates about heat on social media, and the extent to which these assumptions are present, we offer recommendations to increase the persuasiveness of NWS heat communication on social media.

© 2023 American Meteorological Society. This published article is licensed under the terms of the default AMS reuse license. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).

Corresponding author: Michele K. Olson, mkolson@albany.edu

Abstract

Heat communication interventions are an essential way that public safety organizations can reduce extreme heat consequences for at-risk groups. Although the aim of these interventions is typically behavior change, these organizations commonly assume that providing information about heat risks, impacts, vulnerable populations, and protective actions will lead individuals to protect themselves. However, behavior change is a complex process whereby messages must be crafted in ways that increase their persuasive effects. To examine the extent to which key assumptions about behavior change are present in public safety organizations’ heat communication interventions, we examine 250 heat-related tweets sent by seven National Weather Service (NWS) weather forecast offices (WFOs) in 2021. We find that these NWS WFOs use technical language or “jargon” to communicate about heat risks and impacts. In addition, we find that information about vulnerable populations and protective actions is not presented in a way that conforms to theory on behavior change. Based on these results, we offer recommendations to increase the persuasiveness of NWS WFO communication interventions that encourage the public to protect themselves during extreme heat events.

Significance Statement

Heat is the leading cause of death among all weather-related hazards. How heat is communicated to the public can help mitigate heat-related morbidity and mortality. However, heat communication interventions are often developed with several embedded assumptions about behavior change that negatively impact their effectiveness. By examining how a key public safety organization communicates about heat on social media, and the extent to which these assumptions are present, we offer recommendations to increase the persuasiveness of NWS heat communication on social media.

© 2023 American Meteorological Society. This published article is licensed under the terms of the default AMS reuse license. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).

Corresponding author: Michele K. Olson, mkolson@albany.edu
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  • Abrahamson, V., J. Wolf, I. Lorenzoni, B. Fenn, S. Kovats, P. Wilkinson, W. N. Adger, and R. Raine, 2009: Perceptions of heatwave risks to health: Interview-based study of older people in London and Norwich, UK. J. Public Health, 31, 119126, https://doi.org/10.1093/pubmed/fdn102.

    • Search Google Scholar
    • Export Citation
  • Anderson, G. B., and M. L. Bell, 2011: Heat waves in the United States: Mortality risk during heat waves and effect modification by heat wave characteristics in 43 US communities. Environ. Health Perspect., 119, 210218, https://doi.org/10.1289/ehp.1002313.

    • Search Google Scholar
    • Export Citation
  • Ban, J., W. Shi, L. Cui, X. Liu, C. Jiang, L. Han, R. Wang, and T. Li, 2019: Health-risk perception and its mediating effect on protective behavioral adaptation to heat waves. Environ. Res., 172, 2733, https://doi.org/10.1016/j.envres.2019.01.006.

    • Search Google Scholar
    • Export Citation
  • Banwell, C., J. Dixon, H. Bambrick, F. Edwards, and T. Kjellström, 2012: Socio-cultural reflections on heat in Australia with implications for health and climate change adaptation. Global Health Action, 5, 19277, https://doi.org/10.3402/gha.v5i0.19277.

    • Search Google Scholar
    • Export Citation
  • Bassil, K. L., and D. C. Cole, 2010: Effectiveness of public health interventions in reducing morbidity and mortality during heat episodes: A structured review. Int. J. Environ. Res. Public Health, 7, 9911001, https://doi.org/10.3390/ijerph7030991.

    • Search Google Scholar
    • Export Citation
  • Bean, H., N. Grevstad, A. Meyer, and A. Koutsoukos, 2022: Exploring whether wireless emergency alerts can help impede the spread of Covid‐19. J. Contingencies Crisis Manage., 30, 185203, https://doi.org/10.1111/1468-5973.12376.

    • Search Google Scholar
    • Export Citation
  • Benmarhnia, T., L. Schwarz, A. Nori-Sarma, and M. L. Bell, 2019: Quantifying the impact of changing the threshold of New York City heat emergency plan in reducing heat-related illnesses. Environ. Res. Lett., 14, 114006, https://doi.org/10.1088/1748-9326/ab402e.

    • Search Google Scholar
    • Export Citation
  • Casanueva, A., and Coauthors, 2019: Overview of existing heat-health warning systems in Europe. Int. J. Environ. Res. Public Health, 16, 2657, https://doi.org/10.3390/ijerph16152657.

    • Search Google Scholar
    • Export Citation
  • Centers for Disease Control and Prevention, 2017: Warning signs and symptoms of heat-related illness. CDC, https://www.cdc.gov/disasters/extremeheat/warning.html.

  • Centers for Disease Control and Prevention, 2021: Older adults and extreme heat. CDC, https://www.cdc.gov/aging/emergency-preparedness/older-adults-extreme-heat/index.html.

  • Cheng, J., Z. Xu, H. Bambrick, H. Su, S. Tong, and W. Hu, 2018: Heatwave and elderly mortality: An evaluation of death burden and health costs considering short-term mortality displacement. Environ. Int., 115, 334342, https://doi.org/10.1016/j.envint.2018.03.041.

    • Search Google Scholar
    • Export Citation
  • Conti, A., M. Valente, M. Paganini, M. Farsoni, L. Ragazzoni, and F. Barone-Adesi, 2022: Knowledge gaps and research priorities on the health effects of heatwaves: A systematic review of reviews. Int. J. Environ. Res. Public Health, 19, 5887, https://doi.org/10.3390/ijerph19105887.

    • Search Google Scholar
    • Export Citation
  • Di Liberto, T., 2021: Astounding heat obliterates all-time records across the Pacific northwest and western Canada in June 2021. NOAA, https://www.climate.gov/news-features/event-tracker/astounding-heat-obliterates-all-time-records-across-pacific-northwest.

  • Dinesh, S., and M. Odabas, 2023: 10 facts about Americans and Twitter as it rebrands to X. Pew Research Center, https://www.pewresearch.org/fact-tank/2022/05/05/10-facts-about-americans-and-twitter/.

  • Dorfman, L., and L. Wallack, 2012: Putting policy into health communication: The role of media advocacy. Public Communication Campaigns, R. E. Rice and C. K. Atkin, Eds., Vol. 3, SAGE Publications, 337–348.

  • Floyd, D. L., S. Prentice‐Dunn, and R. W. Rogers, 2000: A meta‐analysis of research on protection motivation theory. J. Appl. Soc. Psychol., 30, 407429, https://doi.org/10.1111/j.1559-1816.2000.tb02323.x.

    • Search Google Scholar
    • Export Citation
  • Frisby, B. N., D. D. Sellnow, D. R. Lane, S. R. Veil, and T. L. Sellnow, 2013: Instruction in crisis situations: Targeting learning preferences and self-efficacy. Risk Manage., 15, 250271, https://doi.org/10.1057/rm.2013.7.

    • Search Google Scholar
    • Export Citation
  • Frisby, B. N., S. R. Veil, and T. L. Sellnow, 2014: Instructional messages during health-related crises: Essential content for self-protection. Health Commun., 29, 347354, https://doi.org/10.1080/10410236.2012.755604.

    • Search Google Scholar
    • Export Citation
  • Greene, K., and L. S. Brinn, 2003: Messages influencing college women’s tanning bed use: Statistical versus narrative evidence format and a self-assessment to increase perceived susceptibility. J. Health Commun., 8, 443461, https://doi.org/10.1080/713852118.

    • Search Google Scholar
    • Export Citation
  • Grundstein, A. J., and C. A. Williams, 2018: Heat exposure and the general public: Health impacts, risk communication, and mitigation measures. Human Health and Physical Activity During Heat Exposure, Y. Hosokawa, Ed., Springer, 29–43.

  • Grunig, J. E., 1989: Publics, audiences and market segments: Segmentation principles for campaigns. Information Campaigns: Balancing Social Values and Social Change, C. T. Salmon, Ed., SAGE Publications, 199–228.

  • Guido, G., M. Pichierri, C. Rizzo, V. Chieffi, and G. Moschis, 2021: Information processing by elderly consumers: A five-decade review. J. Serv. Mark., 35, 1428, https://doi.org/10.1108/JSM-09-2019-0368.

    • Search Google Scholar
    • Export Citation
  • Hass, A. L., and K. N. Ellis, 2019: Motivation for heat adaption: How perception and exposure affect individual behaviors during hot weather in Knoxville, Tennessee. Atmosphere, 10, 591, https://doi.org/10.3390/atmos10100591.

    • Search Google Scholar
    • Export Citation
  • Hawkins, M. D., V. Brown, and J. Ferrell, 2017: Assessment of NOAA National Weather Service methods to warn for extreme heat events. Wea. Climate Soc., 9, 513, https://doi.org/10.1175/WCAS-D-15-0037.1.

    • Search Google Scholar
    • Export Citation
  • Hayden, M. H., and Coauthors, 2017: Adaptive capacity to extreme heat: Results from a household survey in Houston, Texas. Wea. Climate Soc., 9, 787799, https://doi.org/10.1175/WCAS-D-16-0125.1.

    • Search Google Scholar
    • Export Citation
  • Hondula, D. M., S. Meltzer, R. C. Balling Jr., and P. Iñiguez, 2022: Spatial analysis of United States National Weather Service excessive heat warnings and heat advisories. Bull. Amer. Meteor. Soc., 103, E2017E2031, https://doi.org/10.1175/BAMS-D-21-0069.1.

    • Search Google Scholar
    • Export Citation
  • Kalkstein, A. J., and S. C. Sheridan, 2007: The social impacts of the heat–health watch/warning system in Phoenix, Arizona: Assessing the perceived risk and response of the public. Int. J. Biometeor., 52, 4355, https://doi.org/10.1007/s00484-006-0073-4.

    • Search Google Scholar
    • Export Citation
  • Kemen, J., S. Schäffer-Gemein, J. Grünewald, and T. Kistemann, 2021: Heat perception and coping strategies: A structured interview-based study of elderly people in Cologne, Germany. Int. J. Environ. Res. Public Health, 18, 7495, https://doi.org/10.3390/ijerph18147495.

    • Search Google Scholar
    • Export Citation
  • Klinenberg, E., 2015: Heat Wave: A Social Autopsy of Disaster in Chicago. University of Chicago Press, 320 pp.

  • Kotharkar, R., and A. Ghosh, 2022: Progress in extreme heat management and warning systems: A systematic review of heat-health action plans (1995–2020). Sustainable Cities Soc., 76, 103487, https://doi.org/10.1016/j.scs.2021.103487.

    • Search Google Scholar
    • Export Citation
  • Kuligowski, E. D., N. A. Waugh, J. Sutton, and T. J. Cova, 2023: Ember alerts: Assessing wireless emergency alert messages in wildfires using the warning response model. Nat. Hazards Rev., 24, 04023009, https://doi.org/10.1061/NHREFO.NHENG-1724.

    • Search Google Scholar
    • Export Citation
  • Lambrecht, K., B. J. Hatchett, K. VanderMolen, and B. Feldkircher, 2021: Identifying community values related to heat: Recommendations for forecast and health risk communication. Geosci. Commun., 4, 517525, https://doi.org/10.5194/gc-4-517-2021.

    • Search Google Scholar
    • Export Citation
  • Lane, K., and Coauthors, 2014: Extreme heat awareness and protective behaviors in New York City. J. Urban Health, 91, 403414, https://doi.org/10.1007/s11524-013-9850-7.

    • Search Google Scholar
    • Export Citation
  • Lehman, S., 2020: Drinking more water during hot weather. Verywell Fit, https://www.verywellfit.com/drink-more-water-during-hot-weather-2506918.

  • Li, Y., and P. D. Howe, 2023: Universal or targeted approaches? An experiment about heat risk messaging. Nat. Hazards, 117, 381398, https://doi.org/10.1007/s11069-023-05864-8.

    • Search Google Scholar
    • Export Citation
  • Li, Y., A. L. Hughes, and P. D. Howe, 2018: Communicating crisis with persuasion: Examining official Twitter messages on heat hazards. Proc. 15th ISCRAM Conf., Rochester, NY, Information Systems for Crisis Response and Management, https://idl.iscram.org/files/yajieli/2018/2124_YajieLi_etal2018.pdf.

  • Lindell, M. K., and R. W. Perry, 2012: The protective action decision model: Theoretical modifications and additional evidence. Risk Anal., 32, 616632, https://doi.org/10.1111/j.1539-6924.2011.01647.x.

    • Search Google Scholar
    • Export Citation
  • Lowe, D., K. L. Ebi, and B. Forsberg, 2011: Heatwave early warning systems and adaptation advice to reduce human health consequences of heatwaves. Int. J. Environ. Res. Public Health, 8, 46234648, https://doi.org/10.3390/ijerph8124623.

    • Search Google Scholar
    • Export Citation
  • Madrigano, J., K. Lane, N. Petrovic, M. Ahmed, M. Blum, and T. Matte, 2018: Awareness, risk perception, and protective behaviors for extreme heat and climate change in New York City. Int. J. Environ. Res. Public Health, 15, 1433, https://doi.org/10.3390/ijerph15071433.

    • Search Google Scholar
    • Export Citation
  • Malmquist, A., M. Hjerpe, E. Glaas, H. Karlsson, and T. Lassi, 2022: Elderly people’s perceptions of heat stress and adaptation to heat: An interview study. Int. J. Environ. Res. Public Health, 19, 3775, https://doi.org/10.3390/ijerph19073775.

    • Search Google Scholar
    • Export Citation
  • Matzarakis, A., G. Laschewski, and S. Muthers, 2020: The heat health warning system in Germany—Application and warnings for 2005 to 2019. Atmosphere, 11, 170, https://doi.org/10.3390/atmos11020170.

    • Search Google Scholar
    • Export Citation
  • Mayrhuber, E. A.-S., and Coauthors, 2018: Vulnerability to heatwaves and implications for public health interventions: A scoping review. Environ. Res., 166, 4254, https://doi.org/10.1016/j.envres.2018.05.021.

    • Search Google Scholar
    • Export Citation
  • McLoughlin, N., C. Howarth, and G. Shreedhar, 2023: Changing behavioral responses to heat risk in a warming world: How can communication approaches be improved? Wiley Interdiscip. Rev.: Climate Change, 14, e819, https://doi.org/10.1002/wcc.819.

    • Search Google Scholar
    • Export Citation
  • Mileti, D. S., 2018: PrepTalks: Dr. Dennis Mileti “Modernizing public warning messaging.” U.S. Federal Emergency Management Agency, YouTube, https://www.youtube.com/watch?v=oYya009bc2M.

  • Mileti, D. S., and J. H. Sorensen, 1990: Communication of emergency public warnings: A Social science perspective and state-of-the-art assessment. Oak Ridge National Laboratories, 160 pp., https://doi.org/10.2172/6137387.

  • Mileti, D. S., and L. Peek, 2000: The social psychology of public response to warnings of a nuclear power plant accident. J. Hazard. Mater., 75, 181194, https://doi.org/10.1016/S0304-3894(00)00179-5.

    • Search Google Scholar
    • Export Citation
  • Milne, S., P. Sheeran, and S. Orbell, 2000: Prediction and intervention in health‐related behavior: A meta‐analytic review of protection motivation theory. J. Appl. Soc. Psychol., 30, 106143, https://doi.org/10.1111/j.1559-1816.2000.tb02308.x.

    • Search Google Scholar
    • Export Citation
  • Morss, R. E., C. L. Cuite, J. L. Demuth, W. K. Hallman, and R. L. Shwom, 2018: Is storm surge scary? The influence of hazard, impact, and fear-based messages and individual differences on responses to hurricane risks in the USA. Int. J. Disaster Risk Reduct., 30, 4458, https://doi.org/10.1016/j.ijdrr.2018.01.023.

    • Search Google Scholar
    • Export Citation
  • Murray-Johnson, L., and K. Witte, 2011: Looking toward the future: Health message design strategies. The Routledge Handbook of Health Communication, T. L. Thompson et al., Eds., Lawrence Erlbaum Associates, Inc., 473–495.

  • National Weather Service, 2021: Weather related fatality and injury statistics. NOAA, accessed 22 June 2022, https://www.weather.gov/hazstat/.

  • National Weather Service, 2022: What is the heat index? NOAA, accessed 20 July 2023, https://www.weather.gov/ama/heatindex.

  • Olson, M. K., J. Sutton, S. C. Vos, R. Prestley, S. L. Renshaw, and C. T. Butts, 2019: Build community before the storm: The National Weather Service’s social media engagement. J. Contingencies Crisis Manage., 27, 359373, https://doi.org/10.1111/1468-5973.12267.

    • Search Google Scholar
    • Export Citation
  • Oxman, A. D., and Coauthors, 2022: Health communication in and out of public health emergencies: To persuade or to inform? Health Res. Policy Syst., 20, 28, https://doi.org/10.1186/s12961-022-00828-z.

    • Search Google Scholar
    • Export Citation
  • Potter, S. H., P. V. Kreft, P. Milojev, C. Noble, B. Montz, A. Dhellemmes, R. J. Woods, and S. Gauden-Ing, 2018: The influence of impact-based severe weather warnings on risk perceptions and intended protective actions. Int. J. Disaster Risk Reduct., 30, 3443, https://doi.org/10.1016/j.ijdrr.2018.03.031.

    • Search Google Scholar
    • Export Citation
  • Reynolds, B., and M. W. Seeger, 2005: Crisis and emergency risk communication as an integrative model. J. Health Commun., 10, 4355, https://doi.org/10.1080/10810730590904571.

    • Search Google Scholar
    • Export Citation
  • Ripberger, J. T., C. L. Silva, H. C. Jenkins-Smith, and M. James, 2015: The influence of consequence-based messages on public responses to tornado warnings. Bull. Amer. Meteor. Soc., 96, 577590, https://doi.org/10.1175/BAMS-D-13-00213.1.

    • Search Google Scholar
    • Export Citation
  • Rossi, M. G., and F. Macagno, 2021: The communicative functions of metaphors between explanation and persuasion. Inquiries in Philosophical Pragmatics, F. Macagno and A. Capone, Eds., Springer, 171–191.

  • Seethaler, S., J. H. Evans, C. Gere, and R. M. Rajagopalan, 2019: Science, values, and science communication: Competencies for pushing beyond the deficit model. Sci. Commun., 41, 378388, https://doi.org/10.1177/1075547019847484.

    • Search Google Scholar
    • Export Citation
  • Seneviratne, S. I., and Coauthors, 2021: Weather and climate extreme events in a changing climate. Climate Change 2021: The Physical Science Basis, V. Masson-Delmotte et al., Eds., Cambridge University Press, 1513–1766.

  • Sheridan, S. C., 2007: A survey of public perception and response to heat warnings across four North American cities: An evaluation of municipal effectiveness. Int. J. Biometeor., 52, 315, https://doi.org/10.1007/s00484-006-0052-9.

    • Search Google Scholar
    • Export Citation
  • Silk, K. J., C. K. Atkin, and C. T. Salmon, 2011: Developing effective media campaigns for health promotion. The Routledge Handbook of Health Communication. T. L. Thompson, R. Parrott, and J. F. Nussbaum, Eds., Routledge, 230–246.

  • Silver, A., and J. Andrey, 2019: Public attention to extreme weather as reflected by social media activity. J. Contingencies Crisis Manage., 27, 346358, https://doi.org/10.1111/1468-5973.12265.

    • Search Google Scholar
    • Export Citation
  • Simis, M. J., H. Madden, M. A. Cacciatore, and S. K. Yeo, 2016: The lure of rationality: Why does the deficit model persist in science communication? Public Understanding Sci., 25, 400414, https://doi.org/10.1177/0963662516629749.

    • Search Google Scholar
    • Export Citation
  • Sivle, A. D., and T. Aamodt, 2019: A dialogue‐based weather forecast: Adapting language to end‐users to improve communication. Weather, 74, 436441, https://doi.org/10.1002/wea.3439.

    • Search Google Scholar
    • Export Citation
  • Snyder, L. B., 2007: Health communication campaigns and their impact on behavior. J. Nutr. Educ. Behav., 39, S32S40, https://doi.org/10.1016/j.jneb.2006.09.004.

    • Search Google Scholar
    • Export Citation
  • Steadman, R. G., 1984: A universal scale of apparent temperature. J. Climate Appl. Meteor., 23, 16741687, https://doi.org/10.1175/1520-0450(1984)023<1674:AUSOAT>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Sutton, J., and E. D. Kuligowski, 2019: Alerts and warnings on short messaging channels: Guidance from an expert panel process. Nat. Hazards Rev., 20, 04019002, https://doi.org/10.1061/(ASCE)NH.1527-6996.0000324.

    • Search Google Scholar
    • Export Citation
  • Sutton, J., L. Fischer, and M. M. Wood, 2021: Tornado warning guidance and graphics: Implications of the inclusion of protective action information on perceptions and efficacy. Wea. Climate Soc., 13, 10031014, https://doi.org/10.1175/WCAS-D-21-0097.1.

    • Search Google Scholar
    • Export Citation
  • Trench, B., 2006: Science communication and citizen science: How dead is the deficit model? Ninth Int. Conf. on Public Communication of Science and Technology (PCST-9), Seoul, South Korea, PCST, WB1-07, https://www.pcst.network/wp-content/uploads/2022/05/PCST-2006-Conference-programme.pdf.

  • Twitter, 2022: How to create a thread on Twitter. X Help Center, https://help.twitter.com/en/using-twitter/create-a-thread.

  • Valois, P., D. Talbot, D. Bouchard, J.-S. Renaud, M. Caron, M. Canuel, and N. Arrambourg, 2020: Using the theory of planned behavior to identify key beliefs underlying heat adaptation behaviors in elderly populations. Popul. Environ., 41, 480506, https://doi.org/10.1007/s11111-020-00347-5.

    • Search Google Scholar
    • Export Citation
  • Viswanath, K., R. F. McCloud, and M. A. Bekalu, 2021: Communication, health, and equity: Structural influences. The Routledge Handbook of Health Communication, T. L. Thompson, R. Parrott, and J. F. Nussbaum Eds., Routledge, 426–440.

  • Wänke, M., and L. Reutner, 2010: Pragmatic persuasion or the persuasion paradox. The Psychology of Attitudes and Attitude Change, J. P. Forgas, J. Cooper, and W. D. Crano, Eds., Routledge, 183–198.

  • Washington State Department of Health, 2021: Heat wave 2021. Accessed 21 June 2022, https://doh.wa.gov/emergencies/be-prepared-be-safe/severe-weather-and-natural-disasters/hot-weather-safety/heat-wave-2021.

  • Watson, H., and R. L. Finn, 2014: Social media and the 2013 UK heat wave: Opportunities and challenges for future events. 11th Int. Conf. on Information Systems for Crisis Response and Management, University Park, PA, ISCRAM, https://idl.iscram.org/files/watson/2014/1069_Watson+Finn2014.pdf.

  • Williams, C. A., and A. J. Grundstein, 2018: Children forgotten in hot cars: A mental models approach for improving public health messaging. Inj. Prev., 24, 279287, https://doi.org/10.1136/injuryprev-2016-042261.

    • Search Google Scholar
    • Export Citation
  • Williams, S., and Coauthors, 2022: Evaluating cost benefits from a heat health warning system in Adelaide, South Australia. Aust. N. Z. J. Public Health, 46, 149154, https://doi.org/10.1111/1753-6405.13194.

    • Search Google Scholar
    • Export Citation
  • Witte, K., 1992: Putting the fear back into fear appeals: The extended parallel process model. Commun. Monogr., 59, 329349, https://doi.org/10.1080/03637759209376276.

    • Search Google Scholar
    • Export Citation
  • Wogalter, M. S., V. C. Conzola, and T. L. Smith-Jackson, 2002: Research-based guidelines for warning design and evaluation. Appl. Ergon., 33, 219230, https://doi.org/10.1016/S0003-6870(02)00009-1.

    • Search Google Scholar
    • Export Citation
  • Wood, M. M., D. S. Mileti, H. Bean, B. F. Liu, J. Sutton, and S. Madden, 2018: Milling and public warnings. Environ. Behav., 50, 535566, https://doi.org/10.1177/0013916517709561.

    • Search Google Scholar
    • Export Citation
  • Wu, Y., X. Wang, J. Wu, R. Wang, and S. Yang, 2020: Performance of heat-health warning systems in Shanghai evaluated by using local heat-related illness data. Sci. Total Environ., 715, 136883, https://doi.org/10.1016/j.scitotenv.2020.136883.

    • Search Google Scholar
    • Export Citation
  • Zhao, X., 2020: Health communication campaigns: A brief introduction and call for dialogue. Int. J. Nurs. Sci., 7, S11S15, https://doi.org/10.1016/j.ijnss.2020.04.009.

    • Search Google Scholar
    • Export Citation
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