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Review Article
Public health agencies’ use of social media for communication during pandemics: a scoping review of the literature
Babatunde Abiodun Balogun, Anne Hogden, Nenagh Kemp, Lin Yang, Maria Agaliotis
Osong Public Health Res Perspect. 2023;14(4):235-251.   Published online August 9, 2023
DOI: https://doi.org/10.24171/j.phrp.2023.0095
  • 1,691 View
  • 147 Download
Graphical AbstractGraphical Abstract AbstractAbstract PDF
Public health agencies (PHAs) have increasingly incorporated social media into their communication mix during successive pandemics in the 21st century. However, the quality, timing, and accuracy of their health messages have varied significantly, resulting in mixed outcomes for communication, audience engagement, and pandemic management. This study aimed to identify factors influencing the effectiveness of pandemic-related health messages shared by PHAs on social media and to report their impact on public engagement as documented in the literature. A scoping literature review was conducted following a predefined protocol. An electronic search of 7 relevant databases and 5 grey literature repositories yielded 9,714 papers published between January 2003 and November 2022. Seventy-three papers were deemed eligible and selected for review. The results underscored the insufficiency of social media guidance policies for PHAs. Six themes were identified: message source, message topic, message style, message timing, content credibility and reliability, and message recipient profile. These themes encompassed 20 variables that could inform PHAs’ social media public health communication during pandemics. Additionally, the findings revealed potential interconnectedness among the variables, and this study concluded by proposing a conceptual model that expands upon existing theoretical foundations for developing and evaluating pandemic-related health messaging.
Original Articles
The role of risk perception, risk communication, and demographic factors in COVID-19 preventive behaviors: an online survey in Iran
Mansour Rezaei, Nader Rajabi Gilan, Ali Almasi, Mehdi Khezeli, Fatemeh Jamshidi Nazar, Zahra Jorjoran Shushtari, Yahya Salimi, Farid Najafi, Neda Sarabi, Shahram Saeidi, Saeid Saeidi
Osong Public Health Res Perspect. 2022;13(4):282-289.   Published online August 31, 2022
DOI: https://doi.org/10.24171/j.phrp.2021.0345
  • 2,829 View
  • 57 Download
  • 3 Web of Science
  • 3 Crossref
AbstractAbstract PDF
Objectives
This study investigated preventive behaviors toward coronavirus disease 2019 (COVID-19) and related factors in a Kurdish Iranian sample.
Methods
This online survey was conducted among the population aged 18 and above in Kermanshah Province, in western Iran, in April 2020. Samples were invited and recruited through social media. Data were collected using a questionnaire consisting of 4 sections (questions on demographic variables, risk perception, risk communication, and COVID-19 preventive behaviors) and analyzed using Stata ver. 8.
Results
The Pearson correlation test showed that risk communication was significantly correlated with COVID-19 preventive behaviors (r=0.320, p<0.01). In the final model, where the explanatory power increased with the entry of the risk communication variable, the variables explained a total of 14% of variance in COVID-19 preventive behaviors. Sex (β=−0.482), risk perception (β=0.047), and risk communication (β=0.662) were significant determinants.
Conclusion
Risk communication and risk perception related to COVID-19, as well as being a woman, were determinants of COVID-19 preventive behaviors.

Citations

Citations to this article as recorded by  
  • Understanding Australian Government Risk Communication Early in the COVID-19 Pandemic: Sociodemographics, Risk Attitudes and Media Consumption
    Yiyun Shou, Louise M. Farrer, Amelia Gulliver, Eryn Newman, Philip J. Batterham, Michael Smithson
    Journal of Health Communication.2023; 28(4): 254.     CrossRef
  • Risk perception and avoidance of preventive behavior on the COVID‐19 among cancer patients
    Mehdi Khezeli, Asghar Tavan, Sajjad Narimani, Vahideh Hoseini, Elham Zare Hosseinzadeh, Parisa Motamedi
    Health Science Reports.2023;[Epub]     CrossRef
  • The Role of Risk Communication in Shaping Health-Protective Behavior Amid the COVID-19 Pandemic in Thailand
    Suphunnika Termmee, Bing Wang
    Social Sciences.2023; 12(10): 551.     CrossRef
Joint Association of Screen Time and Physical Activity with Obesity: Findings from the Korea Media Panel Study
Jihyung Shin
Osong Public Health Res Perspect. 2018;9(4):207-212.   Published online August 31, 2018
DOI: https://doi.org/10.24171/j.phrp.2018.9.4.10
  • 9,405 View
  • 93 Download
  • 10 Crossref
AbstractAbstract PDF
Objectives

There is evidence to suggest that sedentary behavior is associated with a higher risk of metabolic disease. The aim of this study was to investigate cross-sectional joint associations of physical activity (PA) and screen time (ST), with the risk of obesity in Korean adults.

Methods

The Korea Media Panel Study consisted of a household interview and a self-administered diary survey on media usage over 3 days. ST (hours/day) was defined as the reported daily average hours spent watching television, computing (i.e., desktop, notebook, netbook, tablets), smartphone and video game console use. Cross-sectional associations of obesity (BMI ≥ 25 kg/m2) and the amount of daily ST and PA were examined by logistic regression models adjusting for other possible confounders including alcohol consumption, smoking, depressive symptoms and demographic information. There were 7,808 participants included in the analyses.

Results

Increased ST was significantly associated with the risk of obesity (controlling for other possible confounders), but PA level was not found to be significantly linked. Participants who engaged in screen time > 6 hours per day had a higher incidence of obesity.

Conclusion

This study provides evidence of the association between ST and the increased incidence of obesity measured by BMI, independent of PA amongst Korean adults.

Citations

Citations to this article as recorded by  
  • Toward an Integrated Consideration of 24 h Movement Guidelines and Nutritional Recommendations
    Elora Fournier, Edyta Łuszczki, Laurie Isacco, Emilie Chanséaume-Bussiere, Céline Gryson, Claire Chambrier, Vicky Drapeau, Jean-Philippe Chaput, David Thivel
    Nutrients.2023; 15(9): 2109.     CrossRef
  • The economic burden of adolescent internet addiction: A Korean health cost case study
    Robert W. Mead, Edward Nall
    The Social Science Journal.2023; : 1.     CrossRef
  • Relación entre actividad física, sedentarismo y obesidad en adultos, Colombia, 2015
    Ana Yibby Forero , Gina Emely Morales , Luis Carlos Forero
    Biomédica.2023; 43(Sp. 3): 99.     CrossRef
  • Assessment of the Lifestyle Changes Experienced by Dental Professionals before and during COVID-19 Lockdown: A Comparative Pilot Study
    Baby John, Vinola Duraisamy, Diana Prem, Balamanikandasrinivasan Chandrasekaran
    World Journal of Dentistry.2022; 13(6): 658.     CrossRef
  • Demographic, Anthropometric and Food Behavior Data towards Healthy Eating in Romania
    Anca Bacârea, Vladimir Constantin Bacârea, Cristina Cînpeanu, Claudiu Teodorescu, Ana Gabriela Seni, Raquel P. F. Guiné, Monica Tarcea
    Foods.2021; 10(3): 487.     CrossRef
  • Some eating habits and physical activity of players performing in e-sports
    D. B. Nikitjuk, I. V. Kobelkova, M. M. Korosteleva
    Sports medicine: research and practice.2021; 11(3): 57.     CrossRef
  • Association of total sedentary behaviour and television viewing with risk of overweight/obesity, type 2 diabetes and hypertension: A dose–response meta‐analysis
    Chunmei Guo, Qionggui Zhou, Dongdong Zhang, Pei Qin, Quanman Li, Gang Tian, Dechen Liu, Xu Chen, Leilei Liu, Feiyan Liu, Cheng Cheng, Ranran Qie, Minghui Han, Shengbing Huang, Xiaoyan Wu, Yang Zhao, Yongcheng Ren, Ming Zhang, Yu Liu, Dongsheng Hu
    Diabetes, Obesity and Metabolism.2020; 22(1): 79.     CrossRef
  • Dietary and Lifestyle Changes During COVID-19 and the Subsequent Lockdowns among Polish Adults: A Cross-Sectional Online Survey PLifeCOVID-19 Study
    Magdalena Górnicka, Małgorzata Ewa Drywień, Monika A. Zielinska, Jadwiga Hamułka
    Nutrients.2020; 12(8): 2324.     CrossRef
  • The Association between Esports Participation, Health and Physical Activity Behaviour
    Michael G Trotter, Tristan J. Coulter, Paul A Davis, Dylan R Poulus, Remco Polman
    International Journal of Environmental Research an.2020; 17(19): 7329.     CrossRef
  • Associations of Meal Timing and Frequency with Obesity and Metabolic Syndrome among Korean Adults
    Kyungho Ha, YoonJu Song
    Nutrients.2019; 11(10): 2437.     CrossRef
Brief Report
Lyme Disease and YouTubeTM: A Cross-Sectional Study of Video Contents
Corey H. Basch, Lindsay A. Mullican, Kwanza D. Boone, Jingjing Yin, Alyssa Berdnik, Marina E. Eremeeva, Isaac Chun-Hai Fung
Osong Public Health Res Perspect. 2017;8(4):289-292.   Published online August 31, 2017
DOI: https://doi.org/10.24171/j.phrp.2017.8.4.10
  • 4,636 View
  • 31 Download
  • 12 Crossref
AbstractAbstract PDFSupplementary Material
Objectives

Lyme disease is the most common tick-borne disease. People seek health information on Lyme disease from YouTubeTM videos. In this study, we investigated if the contents of Lyme disease-related YouTubeTM videos varied by their sources.

Methods

Most viewed English YouTubeTM videos (n = 100) were identified and manually coded for contents and sources.

Results

Within the sample, 40 videos were consumer-generated, 31 were internet-based news, 16 were professional, and 13 were TV news. Compared with consumer-generated videos, TV news videos were more likely to mention celebrities (odds ratio [OR], 10.57; 95% confidence interval [CI], 2.13–52.58), prevention of Lyme disease through wearing protective clothing (OR, 5.63; 95% CI, 1.23–25.76), and spraying insecticides (OR, 7.71; 95% CI, 1.52–39.05).

Conclusion

A majority of the most popular Lyme disease-related YouTubeTM videos were not created by public health professionals. Responsible reporting and creative video-making facilitate Lyme disease education. Partnership with YouTubeTM celebrities to co-develop educational videos may be a future direction.

Citations

Citations to this article as recorded by  
  • Identifying Trusted Sources of Lyme Disease Prevention Information Among Internet Users Connected to Academic Public Health Resources: Internet-Based Survey Study
    Heather L Kopsco, Rayda K Krell, Thomas N Mather, Neeta P Connally
    JMIR Formative Research.2023; 7: e43516.     CrossRef
  • Identifying Potential Lyme Disease Cases Using Self-Reported Worldwide Tweets: Deep Learning Modeling Approach Enhanced With Sentimental Words Through Emojis
    Elda Kokoe Elolo Laison, Mohamed Hamza Ibrahim, Srikanth Boligarla, Jiaxin Li, Raja Mahadevan, Austen Ng, Venkataraman Muthuramalingam, Wee Yi Lee, Yijun Yin, Bouchra R Nasri
    Journal of Medical Internet Research.2023; 25: e47014.     CrossRef
  • Approaches to Research Ethics in Health Research on YouTube: Systematic Review
    Joshua P Tanner, Courtney Takats, Hannah Stuart Lathan, Amy Kwan, Rachel Wormer, Diana Romero, Heidi E Jones
    Journal of Medical Internet Research.2023; 25: e43060.     CrossRef
  • Leveraging machine learning approaches for predicting potential Lyme disease cases and incidence rates in the United States using Twitter
    Srikanth Boligarla, Elda Kokoè Elolo Laison, Jiaxin Li, Raja Mahadevan, Austen Ng, Yangming Lin, Mamadou Yamar Thioub, Bruce Huang, Mohamed Hamza Ibrahim, Bouchra Nasri
    BMC Medical Informatics and Decision Making.2023;[Epub]     CrossRef
  • Assessing Public Tick Identification Ability and Tick Bite Riskiness Using Passive Photograph-Based Crowdsourced Tick Surveillance
    Heather L Kopsco, Roland J Duhaime, Thomas N Mather, Holly Gaff
    Journal of Medical Entomology.2021; 58(2): 837.     CrossRef
  • Spray Safe, Play Safe: Story-Based Films Increase Homeowner Confidence About Backyard Tick Management
    Victoria L Hornbostel, Rayda K Krell, Jennifer J Reid, Brittany L Schappach, Scott Volpe, Neeta P Connally, Holly Gaff
    Journal of Medical Entomology.2021; 58(2): 857.     CrossRef
  • Cross‐sectional study on the quality of oral lichen planus videos on YouTube™
    Antonio Romano, Dorina Lauritano, Fausto Fiori, Marco Di Petrillo, Iquebal Hasan, Alberta Lucchese, Rosario Serpico, Dario Di Stasio
    Journal of Oral Pathology & Medicine.2021; 50(2): 220.     CrossRef
  • Experience and knowledge of Lyme disease: A scoping review of patient-provider communication
    Anna T. Nesgos, Laura C. Harrington, Emily M. Mader
    Ticks and Tick-borne Diseases.2021; 12(4): 101714.     CrossRef
  • The Coronavirus Intervention in Ethiopia and the Challenges for Implementation
    Hagos Nigussie
    Frontiers in Communication.2021;[Epub]     CrossRef
  • Lyme disease prevention: A content analysis of Canadian patient group and government websites
    Audrey‐Ann Journault, Lucie Richard, Cécile Aenishaenslin
    Zoonoses and Public Health.2020; 67(2): 177.     CrossRef
  • Mapping tweets to a known disease epidemiology; a case study of Lyme disease in the United Kingdom and Republic of Ireland
    John S.P. Tulloch, Roberto Vivancos, Rob M. Christley, Alan D. Radford, Jenny C. Warner
    Journal of Biomedical Informatics.2019; 100: 100060.     CrossRef
  • Eastern Equine Encephalitis and YouTube videos: A content analysis
    Corey H. Basch, Elizabeth B. Blankenship, Isaac Chun-Hai Fung, Christina C. Yarborough, R. Christopher Rustin, Jingjing Yin
    Infection, Disease & Health.2018; 23(4): 197.     CrossRef
Original Article
The Influence of Media Communication on Risk Perception and Behavior Related to Mad Cow Disease in South Korea
Jee-Eun Park, Aeree Sohn
Osong Public Health Res Perspect. 2013;4(4):203-208.   Published online August 31, 2013
DOI: https://doi.org/10.1016/j.phrp.2013.06.005
  • 2,759 View
  • 14 Download
  • 9 Crossref
AbstractAbstract PDF
Objectives
The purpose of this study was to ascertain the influence of media communication on risk behavior related to mad cow disease (MCD).
Methods
Mothers of elementary school students in Seoul were recruited as the survey participants of this study.
Results
Media reports affected risk behavior related to MCD. Also, knowledge and attitude toward MCD affects risk behavior.
Conclusion
Risk-related information provided by the media should maintain consistency and objectivity. For effective risk communication, there should be an open communication between the government and public, experts, and related industries, who should all collaborate.

Citations

Citations to this article as recorded by  
  • The influence of media consumption on public risk perception: a meta-analysis
    Chunhua Niu, Zhixin Jiang, Hongbing Liu, Kehu Yang, Xuping Song, Zhihong Li
    Journal of Risk Research.2022; 25(1): 21.     CrossRef
  • Patterns of compliance with COVID-19 preventive measures among the public in Qatar and Kuwait
    Noora Lari, Noor Al-Thani
    Global Social Policy.2022; 22(3): 580.     CrossRef
  • Understanding risk perception from floods: a case study from China
    Yi Ge, Guangfei Yang, Xiaotao Wang, Wen Dou, Xueer Lu, Jie Mao
    Natural Hazards.2021; 105(3): 3119.     CrossRef
  • When beef consumption becomes politicized: Longitudinal change of US beef purchase intention and political values in Korea
    Byeong Je Kim, Ji-Bum Chung
    Food Policy.2021; 105: 102171.     CrossRef
  • Community participation effects on preparedness behaviour through risk perception: Empirical data of hazardous chemicals from China
    Xiaowei Li, Tiezhong Liu
    International Journal of Disaster Risk Reduction.2020; 44: 101421.     CrossRef
  • Food risk communication: analysis of the media coverage of food risk on Italian online daily newspapers
    Barbara Tiozzo, Anna Pinto, Federico Neresini, Stefano Sbalchiero, Nicoletta Parise, Mirko Ruzza, Licia Ravarotto
    Quality & Quantity.2019; 53(6): 2843.     CrossRef
  • Perceived risks of produced water management and naturally occurring radioactive material content in North Dakota
    Luisa Torres, Om Prakash Yadav, Eakalak Khan
    Journal of Environmental Management.2017; 196: 56.     CrossRef
  • Risk prediction of product-harm events using rough sets and multiple classifier fusion: an experimental study of listed companies in China
    Delu Wang, Jianping Zheng, Gang Ma, Xuefeng Song, Yun Liu
    Expert Systems.2016; 33(3): 254.     CrossRef
  • Health Literacy, Health Risk Perception and Health Behavior of Elders
    Jeong Hee Jeong, Jung Soon Kim
    Journal of Korean Academy of Community Health Nurs.2014; 25(1): 65.     CrossRef

PHRP : Osong Public Health and Research Perspectives