Text analysis of billboards and infographic graphics advertising COVID-19 on promoting preventive behaviors and taking vaccination against the coronavirus pandemic and investigating the opinions of the Iranian adult population

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Abstract

Background

Advertising is one of the most important solutions that health centers and medical services around the world use to try to encourage public opinion to create a positive attitude towards preventive measures and vaccination. This study has been done with the aim of text analysis of billboards and infographics related to promoting preventive behaviors and vaccination against the coronavirus pandemic and providing solutions and models for preventive information and advertising in the field of health.

Methods

The study method in this research is a combination of qualitative and content analysis. Data collection was done in a targeted manner. The sample size includes 33 advertising billboards and infographics. Data collection has been done through searching the sites and websites of health networks and medical education centers in Iran, taking pictures of infographics and billboards in public places, and also receiving archive files of pictures from the public relations of health networks and medical services. The data was collected from February 19, 2020 to December 30, 2022 (the time frame of the pandemic and public vaccination program in Iran). The data was analyzed based on the three-dimensional discourse analysis theory of Fairclough. Then, an online survey about promoting preventive behaviors and vaccination against the coronavirus pandemic in the format of billboards and infographics was designed in SurveyMonkey and its link was provided to the audience through virtual networks and other platforms. The age group of people was selected from 18 to 70 years. Considering that the number of participants should be representative of the entire community under investigation, therefore, based on Cochran’s formula, the sample size was equal to 350 people. Finally, users’ opinions were analyzed using descriptive statistics. The assessment of validity involved experts in infection control and linguistics. The reliability of the measurement, determined through the Cronbach’s alpha internal consistency coefficient, yielded a coefficient of 0.968.

Results

The results show that among the four linguistic components of words, syntax, coherence and text structure; “live metaphors”, “pronoun “we”, “collocation and reference”, and “attitude markers” have the most impact on the audience. The frequency percentage of the data shows that these language elements have tremendous power in attracting the audience to perform preventive behaviors. The results show that the language reflects the culture, opinions and needs of people in the society. Also, the results show that encouraging people to perform preventive behaviors should be through the integration of medical information with motivational linguistic factors in order to attract the audience more.

Conclusions

It can be concluded that the use of the appropriate pattern of medical advertising discourse and correct communication strategies, will help public participation in the field of epidemic control. The language of effective health education and health communication during an epidemic must be related to the ways of thinking and speaking of ordinary people. Also, words with metaphorical and ironic meanings have a high potential to influence the health performance of people in society and increase public awareness of health communication. Therefore, using them to create a new value system with the aim of controlling and overcoming the consequences of the epidemic is very effective.

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Most cited references 32

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Correlation of Chest CT and RT-PCR Testing in Coronavirus Disease 2019 (COVID-19) in China: A Report of 1014 Cases

Tao Ai, Zhenlu Yang, Hongyan Hou … (2020)

Background Chest CT is used for diagnosis of 2019 novel coronavirus disease (COVID-19), as an important complement to the reverse-transcription polymerase chain reaction (RT-PCR) tests. Purpose To investigate the diagnostic value and consistency of chest CT as compared with comparison to RT-PCR assay in COVID-19. Methods From January 6 to February 6, 2020, 1014 patients in Wuhan, China who underwent both chest CT and RT-PCR tests were included. With RT-PCR as reference standard, the performance of chest CT in diagnosing COVID-19 was assessed. Besides, for patients with multiple RT-PCR assays, the dynamic conversion of RT-PCR results (negative to positive, positive to negative, respectively) was analyzed as compared with serial chest CT scans for those with time-interval of 4 days or more. Results Of 1014 patients, 59% (601/1014) had positive RT-PCR results, and 88% (888/1014) had positive chest CT scans. The sensitivity of chest CT in suggesting COVID-19 was 97% (95%CI, 95-98%, 580/601 patients) based on positive RT-PCR results. In patients with negative RT-PCR results, 75% (308/413) had positive chest CT findings; of 308, 48% were considered as highly likely cases, with 33% as probable cases. By analysis of serial RT-PCR assays and CT scans, the mean interval time between the initial negative to positive RT-PCR results was 5.1 ± 1.5 days; the initial positive to subsequent negative RT-PCR result was 6.9 ± 2.3 days). 60% to 93% of cases had initial positive CT consistent with COVID-19 prior (or parallel) to the initial positive RT-PCR results. 42% (24/57) cases showed improvement in follow-up chest CT scans before the RT-PCR results turning negative. Conclusion Chest CT has a high sensitivity for diagnosis of COVID-19. Chest CT may be considered as a primary tool for the current COVID-19 detection in epidemic areas. A translation of this abstract in Farsi is available in the supplement. - ترجمه چکیده این مقاله به فارسی، در ضمیمه موجود است.

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Cancer patients in SARS-CoV-2 infection: a nationwide analysis in China

Wenhua Liang, Weijie Guan, Ruchong Chen … (2020)

China and the rest of the world are experiencing an outbreak of a novel betacoronavirus known as severe acute respiratory syndrome corona virus 2 (SARS-CoV-2). 1 By Feb 12, 2020, the rapid spread of the virus had caused 42 747 cases and 1017 deaths in China and cases have been reported in 25 countries, including the USA, Japan, and Spain. WHO has declared 2019 novel coronavirus disease (COVID-19), caused by SARS-CoV-2, a public health emergency of international concern. In contrast to severe acute respiratory system coronavirus and Middle East respiratory syndrome coronavirus, more deaths from COVID-19 have been caused by multiple organ dysfunction syndrome rather than respiratory failure, 2 which might be attributable to the widespread distribution of angiotensin converting enzyme 2—the functional receptor for SARS-CoV-2—in multiple organs.3, 4 Patients with cancer are more susceptible to infection than individuals without cancer because of their systemic immunosuppressive state caused by the malignancy and anticancer treatments, such as chemotherapy or surgery.5, 6, 7, 8 Therefore, these patients might be at increased risk of COVID-19 and have a poorer prognosis. On behalf of the National Clinical Research Center for Respiratory Disease, we worked together with the National Health Commission of the People's Republic of China to establish a prospective cohort to monitor COVID-19 cases throughout China. As of the data cutoff on Jan 31, 2020, we have collected and analysed 2007 cases from 575 hospitals (appendix pp 4–9 for a full list) in 31 provincial administrative regions. All cases were diagnosed with laboratory-confirmed COVID-19 acute respiratory disease and were admitted to hospital. We excluded 417 cases because of insufficient records of previous disease history. 18 (1%; 95% CI 0·61–1·65) of 1590 COVID-19 cases had a history of cancer, which seems to be higher than the incidence of cancer in the overall Chinese population (285·83 [0·29%] per 100 000 people, according to 2015 cancer epidemiology statistics 9 ). Detailed information about the 18 patients with cancer with COVID-19 is summarised in the appendix (p 1). Lung cancer was the most frequent type (five [28%] of 18 patients). Four (25%) of 16 patients (two of the 18 patients had unknown treatment status) with cancer with COVID-19 had received chemotherapy or surgery within the past month, and the other 12 (25%) patients were cancer survivors in routine follow-up after primary resection. Compared with patients without cancer, patients with cancer were older (mean age 63·1 years [SD 12·1] vs 48·7 years [16·2]), more likely to have a history of smoking (four [22%] of 18 patients vs 107 [7%] of 1572 patients), had more polypnea (eight [47%] of 17 patients vs 323 [23%] of 1377 patients; some data were missing on polypnea), and more severe baseline CT manifestation (17 [94%] of 18 patients vs 1113 [71%] of 1572 patients), but had no significant differences in sex, other baseline symptoms, other comorbidities, or baseline severity of x-ray (appendix p 2). Most importantly, patients with cancer were observed to have a higher risk of severe events (a composite endpoint defined as the percentage of patients being admitted to the intensive care unit requiring invasive ventilation, or death) compared with patients without cancer (seven [39%] of 18 patients vs 124 [8%] of 1572 patients; Fisher's exact p=0·0003). We observed similar results when the severe events were defined both by the above objective events and physician evaluation (nine [50%] of 18 patients vs 245 [16%] of 1572 patients; Fisher's exact p=0·0008). Moreover, patients who underwent chemotherapy or surgery in the past month had a numerically higher risk (three [75%] of four patients) of clinically severe events than did those not receiving chemotherapy or surgery (six [43%] of 14 patients; figure ). These odds were further confirmed by logistic regression (odds ratio [OR] 5·34, 95% CI 1·80–16·18; p=0·0026) after adjusting for other risk factors, including age, smoking history, and other comorbidities. Cancer history represented the highest risk for severe events (appendix p 3). Among patients with cancer, older age was the only risk factor for severe events (OR 1·43, 95% CI 0·97–2·12; p=0·072). Patients with lung cancer did not have a higher probability of severe events compared with patients with other cancer types (one [20%] of five patients with lung cancer vs eight [62%] of 13 patients with other types of cancer; p=0·294). Additionally, we used a Cox regression model to evaluate the time-dependent hazards of developing severe events, and found that patients with cancer deteriorated more rapidly than those without cancer (median time to severe events 13 days [IQR 6–15] vs 43 days [20–not reached]; p<0·0001; hazard ratio 3·56, 95% CI 1·65–7·69, after adjusting for age; figure). Figure Severe events in patients without cancer, cancer survivors, and patients with cancer (A) and risks of developing severe events for patients with cancer and patients without cancer (B) ICU=intensive care unit. In this study, we analysed the risk for severe COVID-19 in patients with cancer for the first time, to our knowledge; only by nationwide analysis can we follow up patients with rare but important comorbidities, such as cancer. We found that patients with cancer might have a higher risk of COVID-19 than individuals without cancer. Additionally, we showed that patients with cancer had poorer outcomes from COVID-19, providing a timely reminder to physicians that more intensive attention should be paid to patients with cancer, in case of rapid deterioration. Therefore, we propose three major strategies for patients with cancer in this COVID-19 crisis, and in future attacks of severe infectious diseases. First, an intentional postponing of adjuvant chemotherapy or elective surgery for stable cancer should be considered in endemic areas. Second, stronger personal protection provisions should be made for patients with cancer or cancer survivors. Third, more intensive surveillance or treatment should be considered when patients with cancer are infected with SARS-CoV-2, especially in older patients or those with other comorbidities.

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Antibody responses to SARS-CoV-2 in patients of novel coronavirus disease 2019

Juanjuan Zhao, Quan Yuan, Haiyan Wang … (2020)

Abstract Background The novel coronavirus SARS-CoV-2 is a newly emerging virus. The antibody response in infected patient remains largely unknown, and the clinical values of antibody testing have not been fully demonstrated. Methods A total of 173 patients with SARS-CoV-2 infection were enrolled. Their serial plasma samples (n=535) collected during the hospitalization were tested for total antibodies (Ab), IgM and IgG against SARS-CoV-2. The dynamics of antibodies with the disease progress was analyzed. Results Among 173 patients, the seroconversion rate for Ab, IgM and IgG was 93.1%, 82.7% and 64.7%, respectively. The reason for the negative antibody findings in 12 patients might due to the lack of blood samples at the later stage of illness. The median seroconversion time for Ab, IgM and then IgG were day-11, day-12 and day-14, separately. The presence of antibodies was <40% among patients within 1-week since onset, and rapidly increased to 100.0% (Ab), 94.3% (IgM) and 79.8% (IgG) since day-15 after onset. In contrast, RNA detectability decreased from 66.7% (58/87) in samples collected before day-7 to 45.5% (25/55) during day 15-39. Combining RNA and antibody detections significantly improved the sensitivity of pathogenic diagnosis for COVID-19 (p<0.001), even in early phase of 1-week since onset (p=0.007). Moreover, a higher titer of Ab was independently associated with a worse clinical classification (p=0.006). Conclusions The antibody detection offers vital clinical information during the course of SARS-CoV-2 infection. The findings provide strong empirical support for the routine application of serological testing in the diagnosis and management of COVID-19 patients.

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Author and article information

Contributors

Mehrdad Askarian: askariam@sums.ac.ir

Journal

Journal ID (nlm-ta): BMC Public Health

Journal ID (iso-abbrev): BMC Public Health

Title: BMC Public Health

Publisher: BioMed Central (London )

ISSN (Electronic): 1471-2458

Publication date (Electronic): 1 March 2024

Publication date PMC-release: 1 March 2024

Publication date Collection: 2024

Volume: 24

Electronic Location Identifier: 651

Affiliations

[1 ]Department of Community Medicine, School of Medicine, Shiraz University of Medical Sciences, ( https://ror.org/01n3s4692) Shiraz, Iran

[2 ]Department of Community Health and Epidemiology, University of Saskatchewan, ( https://ror.org/010x8gc63) Saskatoon, Canada

[3 ]College of Arts & Science, University of Saskatchewan, ( https://ror.org/010x8gc63) Saskatoon, Canada

Article

Publisher ID: 18135

DOI: 10.1186/s12889-024-18135-3

PMC ID: 10905937

PubMed ID: 38429731

SO-VID: f4431107-55c1-42c4-a652-62157bf9c962

License:

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

History

Date received : 13 October 2023

Date accepted : 17 February 2024

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ScienceOpen disciplines: Public health

Keywords: coronavirus,communication,mass media,disease prevention,medical education

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ScienceOpen disciplines: Public health

Keywords: coronavirus, communication, mass media, disease prevention, medical education

Text analysis of billboards and infographic graphics advertising COVID-19 on promoting preventive behaviors and taking vaccination against the coronavirus pandemic and investigating the opinions of the Iranian adult population

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Novel Coronavirus Disease COVID-19

Most cited references 32

Correlation of Chest CT and RT-PCR Testing in Coronavirus Disease 2019 (COVID-19) in China: A Report of 1014 Cases

Cancer patients in SARS-CoV-2 infection: a nationwide analysis in China

Antibody responses to SARS-CoV-2 in patients of novel coronavirus disease 2019

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