Comparative analysis of health authorities’ spokespersons and health influencers during the COVID-19 pandemic

N. Nurlaela Arief; Andika Putra Pratama; Vinka Amalia Hasta Barata; Nyayu Lathifah Tirdasari; Dicky Budiman

doi:10.12688/f1000research.126834.2

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Research Article

Revised

Comparative analysis of health authorities’ spokespersons and health influencers during the COVID-19 pandemic

[version 2; peer review: 1 approved]

N. Nurlaela Arief ¹, Andika Putra Pratama¹, Vinka Amalia Hasta Barata¹, Nyayu Lathifah Tirdasari¹, Dicky Budiman²

N. Nurlaela Arief ¹, Andika Putra Pratama¹, [...] Vinka Amalia Hasta Barata¹, Nyayu Lathifah Tirdasari¹, Dicky Budiman²

PUBLISHED 14 Sep 2023

Author details Author details

¹ School of Business and Management, Institut Teknologi Bandung, Bandung, Indonesia, 40132, Indonesia
² School of Medicine, Griffith University, Brisbane, Australia, 4222, Australia

N. Nurlaela Arief
Roles: Conceptualization, Methodology, Supervision, Writing – Original Draft Preparation

Andika Putra Pratama
Roles: Formal Analysis, Writing – Review & Editing

Vinka Amalia Hasta Barata
Roles: Software, Visualization

Nyayu Lathifah Tirdasari
Roles: Methodology, Resources

Dicky Budiman
Roles: Validation, Writing – Review & Editing

OPEN PEER REVIEW

REVIEWER STATUS

This article is included in the Sociology of Health gateway.

This article is included in the Emerging Diseases and Outbreaks gateway.

This article is included in the Global Public Health gateway.

Abstract

The primary purpose of this research is to compare government and non-government spokespersons by examining their roles in educating about COVID-19 vaccines and health services. This study employed comparative factor analysis and non-participatory observation toward the media activity of spokespersons in Indonesia. Using a questionnaire, this study examined the dimensions of public campaigns, risk communication, health and emergency, leadership and communication from Indonesian spokespersons. The data collection was conducted in two stages: a pilot study involving 102 respondents and the actual study involving 276 respondents.
This study found that the highest perceived benefits and behavioral change come from the non-government spokesperson, of which 26.45% and 18.48% of respondents strongly agree, while the lowest is from a government spokesperson with no medical background. This study also found from five-health spokespersons, the best two are occupied by non-government with medical backgrounds, with 31.52% and 29.35% of respondents strongly agree. However, most respondents had high trust in the governments, with 14.49% strongly agreeing. Compared to those from the governmental sector, spokespersons from the non-governmental sector are perceived to induce higher perceived benefits in delivering the message. However, this does not mean there is no utility in using governmental sector spokespersons, as they are also shown to induce high levels of trust. Overall, governmental and non-governmental spokespersons show utility in different communication aspects, highlighting the need for targeted communication strategies. To conclude, these findings demonstrate that government spokespersons for the COVID-19 pandemic in Indonesia receive the same high level of trust as non-government spokespersons regarding communicating health hazards. The public looks forward to the regularity and routine of the leaders who serve as spokespersons in hopes of easing concerns and tension brought on by the ongoing appearance of the Omicron variation in Indonesia.

Keywords

Omicron, Spokesperson, Health Authorities, Risk Communication, Health Influencer.

Corresponding author: N. Nurlaela Arief

Competing interests: No competing interests were disclosed.

Grant information: This research was supported by ITB under the grant of International Join Research with World Class University, year 2022 (SBM.PN.07-2022).
The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Copyright: © 2023 Nurlaela Arief N et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

How to cite: Nurlaela Arief N, Pratama AP, Amalia Hasta Barata V et al. Comparative analysis of health authorities’ spokespersons and health influencers during the COVID-19 pandemic [version 2; peer review: 1 approved]. F1000Research 2023, 12:90 (https://doi.org/10.12688/f1000research.126834.2) First published: 24 Jan 2023, 12:90 (https://doi.org/10.12688/f1000research.126834.1) Latest published: 14 Sep 2023, 12:90 (https://doi.org/10.12688/f1000research.126834.2)

Revised Amendments from Version 1

We have improve the research results:
We have revised the sampling technique.
Added more explanation in part of population and sample
We have revised Questionnaire Validity & Result Validity
Elaborate more explanation in part of discussion

See the authors' detailed response to the review by Hanny Hafiar

Introduction

The government and health authorities have taken various approaches with diverse strategies during the coronavirus disease 2019 (COVID-19) pandemic. Approaches start by informing and forcing the public to participate in disease prevention and persuading reasonable goals for health.¹ In fact, a comprehensive study conducted in seven countries in Europe discussed risk communication during COVID-19: familiarity, compliance, and trust in WHO precautions.² Further, a former study was conducted in ten European countries, the USA,³^,⁴ Japan, and Australia⁵ concerning the importance of maintaining distance, self-isolation, and quarantine, the application of which varies from simple methods, social campaigns, and heavy sanctions if violated.

In global health policy, the World Health Organization (WHO) has provided guidance and coordinated various efforts to deal with COVID-19. However, each country is also fighting the infodemic: the abundance of information, both accurate and inaccurate, makes it difficult for the public to choose which source is prominent, trusted and reliable to support the right decisions for healthy life during the pandemic.

The infodemic phenomenon is arguably getting stronger because of the high use of social media. With information overload, even false and mythical information. If communities are not targeted appropriately, public health instruction and guidance may not address cultural or linguistic barriers adequately. Therefore, health communication is an essential resource for public health campaigns, seeking behavior change and reducing health gaps in the community.⁶

Specifically, the best practice in Indonesia, by compensating for the infodemic, reliable sources of information are needed, and communicators can convey messages effectively. That makes having a high level of critical health literacy particularly important.⁷ Based on the Google year in search 2021, overall trends that were most searched by people in Indonesia, included those related to covid-19, covid-19 vaccines, Adverse Events Following Immunization (AEPI or KIPI), types of covid-19 vaccines, how to check vaccine certificates, how to list of vaccines, and the nearest vaccination facilities.⁸

Discussion about science related to COVID-19 is not easy to design as a public communication campaign. With the increase in the search for science related to COVID-19, the emergence of new models for the formation of hype in science communication and public understanding about science. In this new model, the blame for hypnotizing scientific results and/or the significance of research findings lies not with the traditional structures of public relations and science communication journalists, but with politicians and social media celebrities, with serious consequences for public policy, as perceived in the case of hydroxychloroquine (HCQ) in Brazil.⁹ As another reference previous research in Japan conclude the effectiveness of refutational two-sided messages for risk communication for new vaccines introduced during the COVID-19 pandemic.¹⁰

The outbreak of the COVID-19 pandemic has resulted in preventive and protective action from the government, healthcare professionals, companies, and medical influencers. Since the first vaccine was approved in Indonesia in January 2021, the government of Indonesia has encouraged the public to support the vaccination program.¹¹ Although, in Indonesia, an increasingly widespread anti-vaccine movement in a group of people or community efforts to persuade people to refuse vaccination.¹² In addition, the majority of false information and invalid conclusion were purposively disseminated on social media.

This condition may create a crisis and emerging risks in the health sector due to the lack of timely and accurate health information. Therefore, WHO supported risk communication intervention contributions from every organization. The organizations define risk communication as various communication required through the preparedness, response, and recovery stage of a serious health situation to encourage informed stakeholders, positive behavior change, and trust maintenance.¹³ Social media is responsible for the main channels for spreading COVID-19 misinformation content compared to mass media channels.¹⁴ The freedom of information through social media may allow people to access valid and invalid information. It would also create potential problems as people would share their pros and cons of vaccination without checking the validity of the information. Information sharing is not only considered as a key source of information, but also a factor in cooperation and modeling problem awareness.¹⁵

The Indonesian government, public health practitioners and even health-related influencers collaborate and counterbalance the spread of negative campaigns about vaccine education and related COVID-19. A group of health spokespersons or influencers from a medical background or voluntarily give objections, provide education and socialization, and clarify misinformation about the COVID-19 topic. Previous research pointed out that risk communication determines and influences an understanding of risk perceptions and shapes public perceptions, leading to behavioral intentions in public health risk situations.¹⁶ Accordingly, the purpose of this research is to explore the role of health authorities’ spokespersons and compare government vs non-government spokespersons with the principles of risk communication theory on spokespersons in educating about COVID-19 vaccine and health services in Indonesia. This study has a novelty value because to the best of our knowledge, the exploration of health authorities’ spokespersons during COVID-19 crisis has not been previously discussed in Indonesia. Most of the studies focus on technical aspects, such as treatment & vaccines.

Literature review

Public communication campaign theory

The vaccine refusal in Indonesia and the pro-vaccine against anti-vaccine phenomenon are related to the public communication campaign. It relates to a program as an endeavor aimed at informing or influencing the behavior of a broad audience over a certain period using a set of organized communication strategies and displaying a series of messages mediated in various channels to create collective benefits for individuals and society.¹⁷ The term campaign describes a phase designed to achieve specific goals. Furthermore, its application is so broad that it includes communication strategies to produce various social, political, commercial, and health effects. Hence, the incorporation and implementation of communication campaigns with vaccinations should be well-planned routine and integral vaccination programs.

Former literature¹⁸ concludes several key points in designing and implementing a communication plan, including the two-way communication process and knowledge. However, the essence is to change behavior, and the selected communication tools need to be used creatively to promote the positive vaccine campaign. In addition, strengthening social norms, building public trust, and continuing government competency in handling the pandemic are vital to increasing vaccination intentions.¹⁹

Health risk communication

The pandemic situations have challenged the importance of communicating risk beyond the everyday challenges of environmental, safety, and health risks to audiences. In terms of risk communication, individuals tend to form attitudes about complex risk-related information by emphasizing existing value systems.²⁰ This form of attitude is due to its hard-to-define nature, as the solutions to address it are often uncertain. Health communication commenced by fostering well-being and basic psychological needs has the potential to promote sustainable behavior prevent the infodemic.⁶ Delivering the risk communication efforts to curb the spread of communicable disease.²¹ Although there is broad consensus among health experts, medical professionals, and policymakers regarding the vaccination, there is a required plan on how the information communicates effectively with the public to address their concerns, beliefs, and trust about vaccines.

It is necessary to design collective values that provide proper guidance since the uncertainty associated with vaccination is a significant issue for public health practitioners.²² Previous literature concludes that public relations play an essential role in managing risks and crises as social media can contribute to real-time dialogue, build trust, and motivate the public to take action for risk and crisis communication around health threats.²³ Furthermore, a key mechanism in reducing the spread of misinformation is the timely provision of risk communication regarding the emergency faced.²⁴ The rapid development of the latest technologies during pandemics enables the Indonesian government to implement risk communication messages to reach the public through various channels, including spokespersons. To determine the success of risk communication depends on how the public makes health-related decisions in the face of contradictory information.²⁵ The stream of messages warning and safety are essential to achieve the effectiveness of the communication.²¹

Risk communication before, during, and after a pandemic

Risk communication before, during, and after a pandemic is critical for public health. Before the pandemic, risk communication plays a vital role in preparation and prevention. It helps raise awareness of potential health threats, educates the public about prevention strategies, and creates a groundwork of trust and credibility which can be drawn upon if a pandemic occurs.

During a pandemic, effective risk communication is of paramount importance. It disseminates crucial information about the disease and safety measures, counters misinformation, reassures the public, manages fear and anxiety, and fosters cooperation with health guidelines. It plays a vital role in shaping public behaviour and can significantly influence the trajectory of the pandemic.

After a pandemic, risk communication is essential for facilitating recovery and learning. It continues to guide the public in the aftermath of the crisis, aid in mental and physical recovery, and restore trust and normalcy. Moreover, post-pandemic risk communication involves reviewing and learning from the crisis to improve preparedness and responses to future health emergencies.

Context of health authorities spokesperson

The context of health authority’s spokesperson in this research is health communicators involved in campaigning vaccines agenda, health promotion and preventive action. The chosen government spokespersons, non-government spokespersons, medical practitioners, health influencers, pediatricians, and health service providers in Indonesia. Further, the spokesperson includes those mentioned professions. Previous research defines a spokesperson as a credible person who communicates voluntarily to inform their network regarding specific issues. In several developing countries, effective communication should be ‘pro-poor and ‘pro- vulnerable’.²⁶

Hence, proper communication methods need to be analyzed and implemented. The problem in communicating healthcare information during COVID-19 is informing the message with proper terminology for the public.²⁷ Similarly, former research found that different populations may acquire different perceptions regarding the crisis, and different spokespersons required for different population segments, especially for younger and older generations.²⁸ The presence of a health spokesperson can become an individual bridging the gap of understanding between fact and fake.

In the COVID-19 situation, the health communication is an emergency to control the situation, such as to mitigate the spread and also the public reaction. At this moment, the spokespersons have to deliver the potential consequences of the infodemic. Since then, there must be careful strategic communication to be applied for the emergency.

Comparative research on different spokespersons within a country during a pandemic

Comparative research on different spokespersons within a country during a pandemic is vital for several reasons. First, diverse spokespersons, including public health officials, political figures, and scientists, communicate risks in various ways based on their expertise, perspectives, and public roles. Understanding these differences can help us to understand how different audiences perceive and respond to these messages. This understanding is crucial, as various demographic groups may have different information needs, literacy levels, and trust in different sources of information.

Second, comparison within a single-country context helps identify which types of messages, communication strategies, and communicators are most effective in informing, persuading, and ensuring compliance with public health measures. These findings can lead to better message targeting and tailoring of communication strategies to enhance their impact.

Third, the urgency for comparison stems from the actual consequences of ineffective risk communication during a pandemic. The spread of misinformation, low public compliance with health guidelines, and erosion of trust in public health measures can all be exacerbated by ineffective communication. Identifying the most effective communicators and understanding their approaches can help to mitigate these challenges.

Methods

This study employed comparative factor analysis and non-participatory observation toward the media activity of spokespersons. The health spokespersons were preferred to represent government, medical experts, and non-government or volunteers. The factors of risk and health communication variables were generated from the literature review according to health spokesperson characteristics. The data were collected by an online questionnaire with a seven-point Likert scale. This online assessment tool is preferable when physical restriction contact occurs in this pandemic. The questionnaire was distributed through the researchers’ network by optimizing email, social media, and personally approached by the researchers. Refer to research ethics, this research asked for respondents’ willingness to fill in the questionnaire at the beginning. It also mentioned that all the data are confidential and appropriately used for the research’s purpose. Bias can lead to distorted results and false conclusions. To reduce bias, this study used several points of view within the research team, including health practitioners, communication practitioners, and academics. In addition, a probability sampling technique was utilized due to practical constraints and the nature of study population. The higher sample sizes provide more reliable results. The author first determines the target population to be studied. Because there is already valid data regarding population figures, the sampling technique and the number of samples needed for the study can be determined.

Data collection

Overview

The target respondents are social media users as infodemic recipients from spokespersons in educating about the COVID-19 vaccine and health services in Indonesia. We study it by first mapping the average age of social media users in Indonesia, then collecting data on how many active social media users are in Indonesia. We employed expert judgment and considered the available resources to determine a feasible sample size that would allow for meaningful analysis and interpretation of the data.

The data collection was conducted in two phases. The first phase was a pilot study collecting data from 102 respondents, the second phase was the actual study collecting data from 276 respondents. Respondents mainly were enrolled through an online survey form between March 7–14, 2022 and 9–12 May 2022. Participation in the survey was voluntary and unpaid.

In addition, secondary data by optimizing big data retrieval was carried out in January 2021–July 2021 (Phase 1) and December 2021–February 2022 to determine what topics are circulating in the public regarding COVID-19 education (Phase 2) February and March 2022, to determine Indonesia health spokespersons. The period of monitoring was three months when Omicron occurred, which was December 2021 to February 2022. This secondary data helped the studies to identify the name of the spokespersons (Table 3) which will be assessed with the questionnaire.

Sample

The number of active social media users in Indonesia in 2019–2020 is 150 million (Statista, we are social, 2020). Therefore, the population of the study was 150 million people. Samples were selected using the Slovin formula with a 10% margin of error which is commonly used for large populations (Regression Analysis, Quantitative Research Methods, Firdaus, 2021) and 150 million of population, resulting in the minimum samples of 100 respondents. The equation used n = N/(1+Ne2) = 150,000,000/(1+150,000,000(10%²)) = 100. $n = \frac{150.000.000}{1 + 150.000.000 {(10 %)}^{2}} \approx 100 samples$ . After distributing online questionnaires through the email, social media, and personally approached, this study received 276 final respondents. The English survey form was translated to its native language (Bahasa Indonesia). The questionnaire can be found as Extended data.³⁵ This study aimed to collect data from respondents aged 16–50 years old. The samples were designed randomly with optimized distribution over the network of ITB (Indonesia), and the public.

As shown in Table 1 demographic summary, the respondents come from diverse backgrounds. However, to ensure this research effectiveness, the respondents were asked about their ideal spokesperson preferences in health promotion & preventive action. To test the questionnaire requires a small sample to align the public campaign theory and risk and health communication dimensions, the researchers conducted a pilot study with 102 samples. It is essential to test the validity of the early research framework. Therefore, it needs a minimum of fifty questionnaires. It considers adequate even if the larger sample will represent a better result.²⁹

Table 1. Respondent summary.

Sample variable	N = 276	Percent	Cumulative percent
Age (mean ± σ)	26.08 ± 6.78
Age
16-20 years	42	15.22	15.22
21-25 years	177	64.13	79.35
26-30 years	30	10.87	90.22
31-35 years	8	2.90	93.12
36-40 years	6	2.17	95.29
41-45 years	2	0.72	96.01
more than 45 years	11	3.99	100.00
Sex
Female	158	57.25	57.25
Male	118	42.75	100.00
Employment
Student	217	78.62	78.62
Private Employee	26	9.42	88.04
Civil Servant/Government Employee	10	3.62	91.67
Entrepreneur	10	3.62	95.29
Academician	8	2.90	98.19
Other	5	1.81	100.00
City
Bandung	106	38.41	38.41
Jakarta	85	30.80	69.20
Tangerang	44	15.94	85.14
Bekasi	4	1.45	86.59
Surabaya	3	1.09	87.68
Malang	3	1.09	88.77
Banten	3	1.09	89.86
Bogor	3	1.09	90.94
Depok	3	1.09	92.03
Yogyakarta	3	1.09	93.12
Other	19	6.88	100.00

In total, the questionnaire consists of 54 questions. The component of questionnaire designed and verified by discussion among the expert from medical doctors & the research team.

Ethical issues

The authors state that the work is written with due consideration of ethical standards. The study was conducted following the ethical principles approved by the Ethics Committee of the University on 01 March 2022 (approval number 1132A/IT1.C09.1/TA.00/2022). The research complied with all ethical standards and anonymity; there were no requirements to provide confidential information (name, date of birth or place of residence, etc.). The respondents gave their written consent for the conduct of the research and data processing. The written consent was provided before the survey. Respondents could not proceed to the survey if they were unwilling to provide the consent or quit otherwise.

Data analysis

Data processing was deployed using Ms Excel 2019 for the data cleaning process, then using SPSS 27 to find the distribution of data, whether it is the frequency in each respondent’s answer choices, descriptive statistics (mean, mode, median). The process continued with a data visualization process using Ms Excel and Tableau. Table 2 shows reliability statistics. Each questionnaire item using a Likert scale is tested for reliability using Cronbach’s Alpha, and this study is considered valid and reliable if the value exceeds 0.70. In the second phase, this study acquired 276 respondents.

Table 2. Respondent summary.

Factor	Cronbach’s Alpha	Cronbach’s Alpha based on standardized items	N of items
PC Benefit	0.765	0.777	5
PC Channel	0.810	0.817	11
CB	0.741	0.746	5
RHC	0.769	0.779	7
HPVP	0.853	0.854	5
HS	0.716	0.724	6
LC	0.747	0.749	3

Validity and reliability test were conducted before analyzing the data. A validity test aims to examine the truth of the measurement. The significant score of each item is below 0.05, which indicates that each item is valid. The reliability test was done to check the consistency of the measurement using coefficient α. The questionnaire is considered reliable if the Cronbach alpha > 0.7. Cronbach alpha’s values for all sets of factors (subscales) are more than 0.7. Hence, this study is considered valid and reliable.

Summary statistics, including percentages, were used to analyze the data. We use descriptive statistics, including proportions and graphical representations, such as 100% stacked bar charts to analyze and display the data. The statistical significance of the difference in proportions was tested using a t-test. Additionally, we used graphical representations and simple ranking for summarizing results. Statistical analyses were performed on SPSS. To simplify the analysis of the results, we used code to replace the name of the spokespersons. Table 3 below explains the code for spokesperson.

Table 3. Spokesperson code.

Subject code	Subject name
NGS 1	Non-Government Spokesperson 1
NGS 2	Non-Government Spokesperson 2
GS 1	Government Spokesperson 1
GS 2	Government Spokesperson 2
GS 3	Government Spokesperson 2

Results

Perceived benefit

Table 1 displays respondents’ demographic information, including age, gender, employment, and the respondents’ city. The number of respondents was 276 (female = 57.25%; Male = 42.75%), with an average age of 16–45.³⁵ Their employment status was student, private employee, civil servant/government employee, entrepreneur, academician, and other. The respondents were from 11 cities in Indonesia (Bekasi, Surabaya, Malang, Banten, Bogor, Depok, Yogyakarta and Other cities). All respondents included in this study were examined for eligibility and confirmed eligible.

This question asks the extent to which the message delivered by the spokespersons are beneficial (i.e. Perceived Benefit). Based on the result (Figure 1), it is found that the means of Perceived Benefit for non-governmental medical doctor(s) as spokespersons, specifically for the second one (NGS2, means = 5.53), are relatively higher than for governmental one(s). Particularly for the second non-governmental medical doctor (NGS2), there are more people who strongly agree (26.45%) that the person has a significant influence in communicating messages to people and the communication about COVID-19 in Indonesia, compared to other doctors (below 15%). Particularly interesting is that the governmental, non-medical, official (GS3) has the lowest mean of Perceived Benefit (means = 4.78). The means of Perceived Benefit for the first and second governmental medical doctors are identical to one another (means = 5.23).

Figure 1. Public Campaign vs Perceived Benefit (PCB) in Indonesia.

Behavioral change

This question asks whether the message delivered by the spokespersons provides an incentive to the respondents to change their behavior (i.e. Behavioral Change). Somewhat mirroring from the trend that can be seen from result of Perceived Benefit, the result of Behavioral Change (Figure 2) shows that the perceived impact of the second non-governmental medical doctor in communicating COVID-19-related matters towards self-behavior. With the means of 5.21, respondents tend to agree more with the respective spokesperson (compared to other spokespersons) being able to influence changes in their behavior. Similar to the previous result, the person with the lowest means regarding perceived behavioral change in people after the message is the governmental, non-medical, person (means = 4.68).

Figure 2. Behavioral Change (BC) in Indonesia.

Vaccination promotion

The question asks whether the message delivered by the spokespersons makes the respondents willing to be vaccinated (i.e. Vaccination Promotion). While there are some differences among the means, the differences do not seem to be significant. However, the second spokesperson (non-governmental, medical, doctor) as shown in Figure 3 is shown to induce more people who strongly agree that the person makes them willing to be vaccinated (40.58%). Again, the governmental, non-medical, spokesperson (GS3) is shown to have the lowest means, indicating that the person is less able (compared to the others) to make the respondents willing to be vaccinated.

Figure 3. Vaccination Promotion (VP).

The comparison of health spokesperson

As Figure 4 shows, when asked the extent to which the spokespersons are experts at health-related matters, the first non-governmental, medical, doctor (NGS1) has the highest means (5.88), followed by the second non-governmental, medical, doctor (NGS2, means = 5.78). Governmental, medical, doctors (GS1, GS2) come third and fourth respectively. The governmental, non-medical, spokesperson (GS3) comes last. This figure generally supports the previous results that show people’s agreement with the impact of the non-governmental, medical, doctors as spokespersons regarding COVID-19-related matters.

Figure 4. Health Spokesperson Comparation (HS).

The channels

Regarding the channels perceived (Figure 5) as the most effective and beneficial when it comes to information pertaining to OMICRON, Online media (means = 6.18) and Instagram (means = 6.12) are shown to be the highest. YouTube (means = 5.87), Twitter (means = 5.80), TikTok (means = 5.62), TV (means = 5.61), and WhatsApp (means = 5.08) are within the range of 5-6 of agreement by respondents. The channels perceived to be the least effective and beneficial are Spotify (4.86), Facebook (4.80), Radio (4.70), and Traditional Channel (means = 4.61).

Figure 5. Public Campaign (PC) channel.

Risk and health communication

Figure 6 regarding risk and health communication shows that most respondents (59.09%) tend to strongly agree on RHC03 regarding consequence, which is also the highest percentage, while for the lowest percentage is for RHC06 regarding probabilities (35.45%). The rest, an explanation of the findings on this RHC, can be seen in the Table 4.

Figure 6. Risk and Health Communication (RHC) in Indonesia.

Table 4. Risk and health communication.

Question code	Description
RHC01 Awareness	How discipline you are to wear a mask and keep the distance in public area?
RHC02 Health Promotion	The government through Health Spokesperson encourage the public to implement health protocol at increases in Omicron cases.
RHC03 Consequences	There are consequences of contracting the disease if I do not apply the current health protocol.
RHC04 Voluntariness	I refrain from going on vacation and going home to reduce the risk of adding Omicron cases.
RHC05 Perceived Control	In wave 3, this Omicron variant, there is a greater risk of contracting the disease.
RHC06 Probabilities	By getting a COVID-19 Vaccine, the risk of Omicron becomes less likely.
RHC07 Well-informed Choices	There is a risk of contracting the Omicron virus if I do not follow the government's advice.

Table 4 shows that the value of RHC03 regarding the consequences of contracting the disease is the highest, and the value of RHC06 probabilities by getting a COVID-19 vaccine, there is a less risk of omicron is the lowest. This shows that respondents tend to strongly agree that there will be consequences if they do not comply with the health protocols, leading them to be exposed to the COVID-19, while a low RHC04 value indicates that respondents tend to be disobedient and prefer to go on vacation and go home so that they do not reduce the risk of developing Omicron cases.

Trust

Regarding the extent to which the respondents trust spokespersons from the government (Figure 7), the means (5.30) lie in between “somewhat trust” and “trust.” Most people generally trust the spokespersons from the government (35.14%), followed by those that somewhat trust the government (28.26%).

Figure 7. Trust Government Spokesperson in Indonesia.

Regarding how consistent the spokespersons of their choice providing information regarding OMICRON (Figure 8) in particular, most respondents tend to answer either “consistent” (37.68%) or “somewhat consistent” (33.33%). No one answered “strongly inconsistent.” Overall, the messaging appears to be relatively consistent.

Figure 8. Leadership Communication (LC) consistency.

Regarding how interactive the spokespersons of their choice are towards the public (Figure 9), most respondents tend to answer “interactive” (40.58%), followed by “somewhat interactive” (28.99%). Overall, the means for perceived interaction between the spokespersons and the public is 5.41.

Figure 9. Leadership Communication (LC) directionally.

Regarding the perception of the extent to which public trust (Figure 10) is important towards the leaders in dealing with the pandemic crisis, the respondents overall lean towards agreeing that it is “important” (35.51%) to “highly important” (32.25%). This indicates the importance of public trust.

Figure 10. Leadership Communication (LC) Trust Leaders in Australia.

Discussion

This study compares government with non-government spokespersons using the principles of risk communication theory in order to examine the function of health authorities’ spokespersons in educating Indonesians about the COVID-19 vaccine and healthcare services. In reviewing the literature, no data was found on exploring health authorities’ spokespersons during the COVID-19 crisis. Most studies focus on technical aspects, such as treatment & vaccines. This study employed comparative factor analysis and non-participatory observation to evaluate how audiences perceive a sample of five spokespersons from both government and non-government sources with medical and non-medical backgrounds. The research evaluates how audiences perceive a sample of five spokespersons from both government and non-government sources with medical and non-medical backgrounds, and we replaced the names of the spokespersons with code to make the analysis of the results easier. They are NGS 1 (Non-Government Spokesperson 1), NGS 2 (Non-Government Spokesperson 2), GS 1 (Government Spokesperson 1), GS 2 (Government Spokesperson 2), and GS 3 (Government Spokesperson 3), as mentioned in Table 3. There are two representatives of the non-Government and three representatives of the government. This study collected data from 276 eligible respondents, which were dominated by females (57.25%), aged 21–25 years old (64.13%), students (78.62%), and lived in Bandung (38.41%).

The first question in this study sought to determine the extent to which the spokespersons’ message is beneficial (Perceived Benefit). This study found that the highest perceived benefits come from the non-government spokesperson (Figure 1), particularly NGS 2, which is representative of the non-Government and a medical doctor. Non-government spokesperson gains higher trust than the government. This person is influential in spreading information about COVID-19 in Indonesia and conveying messages to individuals. Another finding is that the lowest mean of Perceived Benefit is GS 3, which is a government spokesperson with no medical background. Risk communication designed and delivered by experts, policymakers, and regulators showed less effective results, especially related to risk & health communication. Risk communication should be carefully designed; it requires a scientize and democratize approach³⁰ especially with issues related to covid, vaccines and uncertain scientific and ethical characteristics.³¹ Risk and health communication has a wide and diverse audience.

The second question in this research was whether the spokespersons’ message incentivizes the respondents to change their behavior (Behavioral Change). Again, this study found that the highest behavioral change comes from a non-government spokesperson with a medical background (Figure 2), and the lowest is from a government spokesperson with no medical background. More often than not, respondents concur that a non-government person with medical background can modify a person’s behavior. Moreover, it is more potent than that of other spokespersons. Finset (2021) found that the difficulty in conveying healthcare information during COVID-19 is using the right words to enlighten the audience.²⁷ This study confirms that proper terminology, mainly healthcare information, is crucial. It is because a person with experience in the health field can explain things clearly using the appropriate language, which motivates behavior change.

The third question of the project was to identify whether the message delivered by the spokespersons made the respondents willing to be vaccinated (Vaccination Promotion). Although there are some disparities in the means, they do not seem significant. However, non-government is able to persuade more people to strongly agree that the person makes them want to receive vaccinations (Figure 3). While government spokesperson is once more found to have the lowest means, showing that they are less effective than the others at persuading respondents to get shots.

The fourth question was designed to compare all the five-health spokespersons. According to respondents, this study found that the best two are occupied by non-government with medical backgrounds (Figure 4). At the same time, the rest are the government with medical background and the government without medical background. This study generally concurs with earlier findings that indicated public acceptance of the value of non-governmental, medical, and doctor spokespersons for COVID-19-related issues.

Atkin and Rice (2012) stated that public communication refers to a program as an endeavor designed to inform or influence the behavior of a large audience over a specific period of time using a set of planned communication strategies and displaying a series of messages mediated through various channels to produce collective benefits for individuals and society.¹⁷ Moreover, the constant flow of messages for communication to be adequate, caution and safety are crucial.²¹ Concerning the channels perceived, it was found that online media is the best and most helpful source of information on OMICRON (Figure 5). At the same time, the remaining are Instagram, YouTube, Twitter, TikTok, tv, WhatsApp, Spotify, Facebook, radio, and traditional channel. This finding is consistent with that of Tirkkonen and Luoma-aho (2011),²³ who mentioned that in order to communicate dangers and crises involving potential health threats effectively, public relations are crucial. Social media may foster real-time discourse, foster trust, and inspire people to take action.

The results show variations in parameters related to risk and health communication, which consist of awareness, health promotion, consequences, voluntariness, perceived control, probabilities, and well-informed choices (Table 4). The majority of respondents (61.59%) prefer to strongly agree with the consequence, which also has the most significant proportion, while regarding probabilities has the lowest number of 39.49% (Figure 6). It demonstrates that the probability of catching the disease has the highest value. In contrast, the probability that receiving the COVID-19 vaccination will result in a lower risk of omicron has the lowest value. While a low voluntariness value indicates that respondents tend to be disobedient and prefer to go on vacation and go home so they do not reduce their risk of developing Omicron cases, it demonstrates that respondents generally strongly agree that there will be consequences if they do not comply with the health protocols, exposing them to the COVID-19. Experts, officials, and regulators who created and delivered risk communication had less success, particularly regarding risk & health communication, than others. Risk communication needs to be adequately planned; it calls for a democratized and scientize strategy, particularly concerning concerns about covid, vaccinations, and other features with ambiguous scientific and ethical implications. Since the audience for risk and health communication is large and diverse, it is vital to create risk communication specifically aimed at that audience. It can be done by developing a personalized communication strategy for people at a high risk of catching a disease.

This study found that most respondents had high trust in the government’s spokesperson (Figure 7). The means (5.30) for the respondents’ level of trust in government spokespersons fall between “somewhat trust” and “trust.” Most people (35.14%) have a general faith in government spokespersons, followed by those with limited trust (28.26%).

In order to combat the infodemic, it is crucial to comprehend vital facts, develop suitable and relevant messages, and disseminate information using the most effective methods. The majority of respondents often choose “consistent” (37.68%) or “somewhat consistent” (33.33%) when asked how consistently the spokespersons of their choosing provide information about OMICRON (Figure 8), in particular. Nobody gave the response “strongly inconsistent.” The messaging seems to be very consistent overall.

Another finding is that most respondents often choose “interactive” (40.58%), followed by “somewhat interactive” (28.99%) when asked how engaging the spokespersons of their choice are with the public (Figure 9). A mean of 5.41 describes how the public perceives interactions between spokespersons and the public. The results of this study show that the respondents generally tilt toward agreeing that it is “important” (35.51%) to “highly important” (32.25%) when asked about how important they believe public trust in the leaders is in dealing with the pandemic crisis (Figure 10). It is clear from this that public trust is essential.

Conclusions

The Indonesian government started to perform a collaborative agenda to support the vaccination campaign, which was carried out amid the current COVID-19 pandemic. The vaccine is one of the expected efforts to end the pandemic. The vaccination campaign implementation in Indonesia is facing a massive scope and complexity. There is always an uncertainty factor in vaccines. A carefully crafted communication strategy should be an integral component of the vaccination program, addressing the specific factors influencing the target/population to assess progress toward achieving herd immunity. Hence, the success of public communication theory relies on the public’s acceptability of vaccination. The research provides valuable insights for communication management and government in developing and supporting the role of health authorities from the government, non-government and medical sectors. Based on the results, several factors emerge as important. The proficiency of medical practitioners cannot determine the spokesperson’s effectiveness. A spokesperson who possesses referent power, expert power, and reward power should be more effective than other spokespersons.³² Furthermore, the more significant the social capabilities that are possessed, the greater the ability to influence the behavior of its network. Another study concluded that a spokesperson’s physical attractiveness to be more persuasive for implementing organizational messages.³³ How the spokesperson deals with the media request and offers an answer as soon as possible to give other media information from other sources can also reflect as a good spokesperson practice.³⁴ In addition, spokespersons in this pandemic play an important role in filling the information gap between the government and the public. The effectiveness of the spokesperson’s implementation is critical in the rapid advancement and change of digital information. Unfortunately, many methods and application techniques were evolving in vain without proper crisis communication-based implementation. The authority of health spokesperson is crucial to respond to public health risk situations. The organization needs to emphasize the vital role of a spokesperson in these circumstances, as one which helps and assists in developing messages sent or delivered to the public. Another important reason for utilizing spokespersons is their capabilities of reaching diverse audiences, public engagement and empowerment, trustworthiness, and credibility. These practices provide valuable indicators for other countries and make a theoretical contribution. This study implies strengthening the preparedness response during a health crisis, especially in risk & crisis communication. The literature has not explored the study of health authorities spokespersons previously. This, combined with the Indonesian perspectives, brings new insights to the field. Social media use is incredibly high in Indonesia, so it acts as a good exemplar for the field. It also builds on the growing literature about the importance of individual and health practitioners as health authorities, especially in the social media space during the COVID-19 crisis.

Limitation and future research

This scoping review has several limitations. First, when the data was collected, Indonesia was experiencing a new type of COVID-19 virus, causing that data collection was not optimal. Second, the literature review on spokespersons was mainly from articles and international reports (e.g., WHO, Satgas COVID), with limited references to the practice of spokespersons in Indonesia and Asia. Thirdly, when grouping spokesperson data presented with big data, many spokesperson figures appeared and were curated to be selected based on the evaluation of the research team. Fourth, some data on spokesperson statements and non-participatory observation are dynamic from time to time and change simultaneously. Therefore, some of the spokespersons as an object of research might have been excluded from this review process.

Data availability

Underlying data

Dryad: Comparative analysis of health authorities spokesperson and health influencer during the COVID-19 pandemic: A case in Indonesia. https://doi.org/10.5061/dryad.12jm63z23.³⁵

This project contains the following underlying data:

- Response_Spokesperson_2 (Responses to survey)

Extended data

Dryad: Comparative analysis of health authorities spokesperson and health influencer during the COVID-19 pandemic: A case in Indonesia. https://doi.org/10.5061/dryad.12jm63z23h.³⁵

This project contains the following extended data:

- Quesionnaire_Spokesperson_1_Rev_(1) (questionnaire - English translation)

Data are available under the terms of the Creative Commons Zero “No rights reserved” data waiver (CC0 1.0 Public domain dedication).

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Version 2

VERSION 2 PUBLISHED 24 Jan 2023

Author details Author details

¹ School of Business and Management, Institut Teknologi Bandung, Bandung, Indonesia, 40132, Indonesia
² School of Medicine, Griffith University, Brisbane, Australia, 4222, Australia

N. Nurlaela Arief
Roles: Conceptualization, Methodology, Supervision, Writing – Original Draft Preparation

Andika Putra Pratama
Roles: Formal Analysis, Writing – Review & Editing

Vinka Amalia Hasta Barata
Roles: Software, Visualization

Nyayu Lathifah Tirdasari
Roles: Methodology, Resources

Dicky Budiman
Roles: Validation, Writing – Review & Editing

Competing interests

No competing interests were disclosed.

Grant information

This research was supported by ITB under the grant of International Join Research with World Class University, year 2022 (SBM.PN.07-2022).
The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

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Nurlaela Arief N, Pratama AP, Amalia Hasta Barata V et al. Comparative analysis of health authorities’ spokespersons and health influencers during the COVID-19 pandemic [version 2; peer review: 1 approved]. F1000Research 2023, 12:90 (https://doi.org/10.12688/f1000research.126834.2)

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Reviewer Report 28 Sep 2023

Hanny Hafiar, Faculty of Communication Science, Universitas Padjajaran Bandung, Bandung, Indonesia

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https://doi.org/10.5256/f1000research.155777.r206679

Thank you for the improvements you have made, so far I think the results of these improvements ... Continue reading

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Reviewer Report 14 Jun 2023

Hanny Hafiar, Faculty of Communication Science, Universitas Padjajaran Bandung, Bandung, Indonesia

Approved with Reservations

https://doi.org/10.5256/f1000research.139284.r175543

I commend the authors for their efforts. I provide my comments for this article as follows:

The abstract section has briefly justified the purpose of this research well, how the research method is applied. I think

I commend the authors for their efforts. I provide my comments for this article as follows:

The abstract section has briefly justified the purpose of this research well, how the research method is applied. I think the keywords are also good and represent the description of the content of this research. However, the author(s) failed to highlight the research results, which are in accordance with the research objective, namely "to compare." What is the outline of the comparison?
The Introduction section is well-written in the present research context. However, this introductory section does not explain in detail why there is a need for this comparative research. What is the urgency why these health communicators should be compared? Researchers tend to emphasize the importance of risk communication only in the context of a pandemic.
The method is still problematic. How does the author(s) determine a representative sample size before carrying out one of the sampling techniques? It seems this research applies non-probability sampling, so does the Slovin formula work enough to determine the sample size for a study with non-probability sampling? Where did the author get the population (150 million)? And why is the margin of error 10%? Is the sample strong enough to produce confident findings? Is this research capable of producing confident results? It seems unclear. The author(s) need to clarify it.
The results section looks fine. However, in the discussion section, the authors seem to have lacked elaboration on the research findings with the literature studies conducted. It makes the manuscript unbalanced between the literature review that underlies this study and the discussion of its findings. The author(s) need to comprehensively discuss the results and what are the implications of these findings.
This article is quite promising, but the author needs to clarify things that are questionable by reviewers or even readers later.

Is the work clearly and accurately presented and does it cite the current literature?

Yes
Is the study design appropriate and is the work technically sound?

Partly
Are sufficient details of methods and analysis provided to allow replication by others?

Partly
If applicable, is the statistical analysis and its interpretation appropriate?

Partly
Are all the source data underlying the results available to ensure full reproducibility?

Yes
Are the conclusions drawn adequately supported by the results?

Yes

Competing Interests: No competing interests were disclosed.

Reviewer Expertise: Health communication; Health promotion

I confirm that I have read this submission and believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard, however I have significant reservations, as outlined above.

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Author Response 14 Sep 2023

Neneng Nurlaela Arief, School of Business and Management, Institut Teknologi Bandung, Bandung, 40132, Indonesia

14 Sep 2023

Author Response

1. The abstract section has briefly justified the purpose of this research well, how the research method is applied. I think the keywords are also good and represent the description ... Continue reading 1. The abstract section has briefly justified the purpose of this research well, how the research method is applied. I think the keywords are also good and represent the description of the content of this research. However, the author(s) failed to highlight the research results, which are in accordance with the research objective, namely "to compare." What is the outline of the comparison?

Authors response:

We have improve the research results:

Results: This study found that the highest perceived benefits and behavioral change come from the non-government spokesperson, of which 26.45% and 18.48% of respondents strongly agree, while the lowest is from a government spokesperson with no medical background. This study also found from five-health spokespersons, the best two are occupied by non-government with medical backgrounds, with 31.52% and 29.35% of respondents strongly agree. However, most respondents had high trust in the governments, with 14.49% strongly agreeing. Compared to those from the governmental sector, spokespersons from the non-governmental sector are perceived to induce higher perceived benefits in delivering the message. However, this does not mean there is no utility in using governmental sector spokespersons, as they are also shown to induce high levels of trust. Overall, governmental and non-governmental spokespersons show utility in different communication aspects, highlighting the need for targeted communication strategies. To conclude, these findings demonstrate that government spokespersons for the COVID-19 pandemic in Indonesia receive the same high level of trust as non-government spokespersons regarding communicating health hazards. The public looks forward to the regularity and routine of the leaders who serve as spokespersons in hopes of easing concerns and tension brought on by the ongoing appearance of the Omicron variation in Indonesia.

2. How does the author(s) determine a representative sample size before carrying out one of the sampling techniques?

Authors response:

Regarding the determination of a representative sample size, we apologize for not providing sufficient clarification in our paper. In our research, we employed a probability sampling technique due to practical constraints and the nature of our study population.
The author first determines the target population to be studied. Because there is already valid data regarding population figures, the sampling technique and the number of samples needed for the study can be determined.

3. This research applies non-probability sampling, so does the Slovin formula work enough to determine the sample size for a study with non-probability sampling?

Authors response:

Probability sampling is used because the population size is known to calculate the required sample size. In determining the respondents are also not limited by specific subjective criteria.
The slovin formula is also appropriate because the slovin formula can be used for the probability sampling method. The slovin technique is a derivative of the Cochran formula and the confidence level is 95% (significance level α=5%).

With a population of 150 million, the required sample size is still 100.

4. Where did the author get the population (150 million)?

Authors response:

The target respondents are social media users as infodemic recipients from spokespersons in educating about the COVID-19 vaccine and health services in Indonesia.

We study it by first mapping the average age of social media users in Indonesia, then collecting data on how many active social media users are in Indonesia. According to several reliable research sources, the number of active social media users in Indonesia in 2019 -2020 is 150 million (Statista, we are social, 2020). Therefore, the population of the study was 150 million people. We employed expert judgment and considered the available resources to determine a feasible sample size that would allow for meaningful analysis and interpretation of the data

5. Why is the margin of error 10%? Is the sample strong enough to produce confident findings?

Authors response:

A 10% margin of error is commonly used for large populations (Regression Analysis, Quantitative Research Methods, Firdaus, 2021). The Slovin formula can be used with the following conditions: e = 0.1 (10%) for a large population, e = 0.02 (20%) for a small population. So the range of samples that can be taken from the Slovin technique is between 10-20% of the study population. Therefore, this study's sample size is appropriate and valid to represent the population. Note: The significance level differs from the margin of error, so the significance level remains low according to the standard (5%).

6. Is this research capable of producing confident results?

Authors response:

- Questionnaire Validity
Before data collection, a pilot study was conducted to test the validity and reliability of the questionnaire. Each questionnaire item was tested using Cronbach's Alpha, the results of which can be seen in Table 2.

- Result Validity
The sampling technique and the number of samples have been determined systematically so that they can represent the population.

Response to reviewer comments No 1 & 4 the abstract section, result & discussion.

Thank you for bringing this important aspect to our attention. Your feedback has been invaluable, and we are committed to incorporating your suggestions to rewrite the abstract, strengthen the introduction and provide a more comprehensive justification for result and discussion section. We will highlight that the findings from such studies can provide valuable insights and evidence-based recommendations for improving communication strategies across diverse health contexts, including but not limited to pandemics.
1. The abstract section has briefly justified the purpose of this research well, how the research method is applied. I think the keywords are also good and represent the description of the content of this research. However, the author(s) failed to highlight the research results, which are in accordance with the research objective, namely "to compare." What is the outline of the comparison?

Authors response:

We have improve the research results:

Results: This study found that the highest perceived benefits and behavioral change come from the non-government spokesperson, of which 26.45% and 18.48% of respondents strongly agree, while the lowest is from a government spokesperson with no medical background. This study also found from five-health spokespersons, the best two are occupied by non-government with medical backgrounds, with 31.52% and 29.35% of respondents strongly agree. However, most respondents had high trust in the governments, with 14.49% strongly agreeing. Compared to those from the governmental sector, spokespersons from the non-governmental sector are perceived to induce higher perceived benefits in delivering the message. However, this does not mean there is no utility in using governmental sector spokespersons, as they are also shown to induce high levels of trust. Overall, governmental and non-governmental spokespersons show utility in different communication aspects, highlighting the need for targeted communication strategies. To conclude, these findings demonstrate that government spokespersons for the COVID-19 pandemic in Indonesia receive the same high level of trust as non-government spokespersons regarding communicating health hazards. The public looks forward to the regularity and routine of the leaders who serve as spokespersons in hopes of easing concerns and tension brought on by the ongoing appearance of the Omicron variation in Indonesia.

2. How does the author(s) determine a representative sample size before carrying out one of the sampling techniques?

Authors response:

Regarding the determination of a representative sample size, we apologize for not providing sufficient clarification in our paper. In our research, we employed a probability sampling technique due to practical constraints and the nature of our study population.
The author first determines the target population to be studied. Because there is already valid data regarding population figures, the sampling technique and the number of samples needed for the study can be determined.

3. This research applies non-probability sampling, so does the Slovin formula work enough to determine the sample size for a study with non-probability sampling?

Authors response:

Probability sampling is used because the population size is known to calculate the required sample size. In determining the respondents are also not limited by specific subjective criteria.
The slovin formula is also appropriate because the slovin formula can be used for the probability sampling method. The slovin technique is a derivative of the Cochran formula and the confidence level is 95% (significance level α=5%).

With a population of 150 million, the required sample size is still 100.

4. Where did the author get the population (150 million)?

Authors response:

The target respondents are social media users as infodemic recipients from spokespersons in educating about the COVID-19 vaccine and health services in Indonesia.

We study it by first mapping the average age of social media users in Indonesia, then collecting data on how many active social media users are in Indonesia. According to several reliable research sources, the number of active social media users in Indonesia in 2019 -2020 is 150 million (Statista, we are social, 2020). Therefore, the population of the study was 150 million people. We employed expert judgment and considered the available resources to determine a feasible sample size that would allow for meaningful analysis and interpretation of the data

5. Why is the margin of error 10%? Is the sample strong enough to produce confident findings?

Authors response:

A 10% margin of error is commonly used for large populations (Regression Analysis, Quantitative Research Methods, Firdaus, 2021). The Slovin formula can be used with the following conditions: e = 0.1 (10%) for a large population, e = 0.02 (20%) for a small population. So the range of samples that can be taken from the Slovin technique is between 10-20% of the study population. Therefore, this study's sample size is appropriate and valid to represent the population. Note: The significance level differs from the margin of error, so the significance level remains low according to the standard (5%).

6. Is this research capable of producing confident results?

Authors response:

- Questionnaire Validity
Before data collection, a pilot study was conducted to test the validity and reliability of the questionnaire. Each questionnaire item was tested using Cronbach's Alpha, the results of which can be seen in Table 2.

- Result Validity
The sampling technique and the number of samples have been determined systematically so that they can represent the population.

Response to reviewer comments No 1 & 4 the abstract section, result & discussion.

Thank you for bringing this important aspect to our attention. Your feedback has been invaluable, and we are committed to incorporating your suggestions to rewrite the abstract, strengthen the introduction and provide a more comprehensive justification for result and discussion section. We will highlight that the findings from such studies can provide valuable insights and evidence-based recommendations for improving communication strategies across diverse health contexts, including but not limited to pandemics.
Competing Interests: No competing interests were disclosed. Close
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Author Response 14 Sep 2023

Neneng Nurlaela Arief, School of Business and Management, Institut Teknologi Bandung, Bandung, 40132, Indonesia

14 Sep 2023

Author Response

1. The abstract section has briefly justified the purpose of this research well, how the research method is applied. I think the keywords are also good and represent the description ... Continue reading 1. The abstract section has briefly justified the purpose of this research well, how the research method is applied. I think the keywords are also good and represent the description of the content of this research. However, the author(s) failed to highlight the research results, which are in accordance with the research objective, namely "to compare." What is the outline of the comparison?

Authors response:

We have improve the research results:

Results: This study found that the highest perceived benefits and behavioral change come from the non-government spokesperson, of which 26.45% and 18.48% of respondents strongly agree, while the lowest is from a government spokesperson with no medical background. This study also found from five-health spokespersons, the best two are occupied by non-government with medical backgrounds, with 31.52% and 29.35% of respondents strongly agree. However, most respondents had high trust in the governments, with 14.49% strongly agreeing. Compared to those from the governmental sector, spokespersons from the non-governmental sector are perceived to induce higher perceived benefits in delivering the message. However, this does not mean there is no utility in using governmental sector spokespersons, as they are also shown to induce high levels of trust. Overall, governmental and non-governmental spokespersons show utility in different communication aspects, highlighting the need for targeted communication strategies. To conclude, these findings demonstrate that government spokespersons for the COVID-19 pandemic in Indonesia receive the same high level of trust as non-government spokespersons regarding communicating health hazards. The public looks forward to the regularity and routine of the leaders who serve as spokespersons in hopes of easing concerns and tension brought on by the ongoing appearance of the Omicron variation in Indonesia.

2. How does the author(s) determine a representative sample size before carrying out one of the sampling techniques?

Authors response:

Regarding the determination of a representative sample size, we apologize for not providing sufficient clarification in our paper. In our research, we employed a probability sampling technique due to practical constraints and the nature of our study population.
The author first determines the target population to be studied. Because there is already valid data regarding population figures, the sampling technique and the number of samples needed for the study can be determined.

3. This research applies non-probability sampling, so does the Slovin formula work enough to determine the sample size for a study with non-probability sampling?

Authors response:

Probability sampling is used because the population size is known to calculate the required sample size. In determining the respondents are also not limited by specific subjective criteria.
The slovin formula is also appropriate because the slovin formula can be used for the probability sampling method. The slovin technique is a derivative of the Cochran formula and the confidence level is 95% (significance level α=5%).

With a population of 150 million, the required sample size is still 100.

4. Where did the author get the population (150 million)?

Authors response:

The target respondents are social media users as infodemic recipients from spokespersons in educating about the COVID-19 vaccine and health services in Indonesia.

We study it by first mapping the average age of social media users in Indonesia, then collecting data on how many active social media users are in Indonesia. According to several reliable research sources, the number of active social media users in Indonesia in 2019 -2020 is 150 million (Statista, we are social, 2020). Therefore, the population of the study was 150 million people. We employed expert judgment and considered the available resources to determine a feasible sample size that would allow for meaningful analysis and interpretation of the data

5. Why is the margin of error 10%? Is the sample strong enough to produce confident findings?

Authors response:

A 10% margin of error is commonly used for large populations (Regression Analysis, Quantitative Research Methods, Firdaus, 2021). The Slovin formula can be used with the following conditions: e = 0.1 (10%) for a large population, e = 0.02 (20%) for a small population. So the range of samples that can be taken from the Slovin technique is between 10-20% of the study population. Therefore, this study's sample size is appropriate and valid to represent the population. Note: The significance level differs from the margin of error, so the significance level remains low according to the standard (5%).

6. Is this research capable of producing confident results?

Authors response:

- Questionnaire Validity
Before data collection, a pilot study was conducted to test the validity and reliability of the questionnaire. Each questionnaire item was tested using Cronbach's Alpha, the results of which can be seen in Table 2.

- Result Validity
The sampling technique and the number of samples have been determined systematically so that they can represent the population.

Response to reviewer comments No 1 & 4 the abstract section, result & discussion.

Thank you for bringing this important aspect to our attention. Your feedback has been invaluable, and we are committed to incorporating your suggestions to rewrite the abstract, strengthen the introduction and provide a more comprehensive justification for result and discussion section. We will highlight that the findings from such studies can provide valuable insights and evidence-based recommendations for improving communication strategies across diverse health contexts, including but not limited to pandemics.
1. The abstract section has briefly justified the purpose of this research well, how the research method is applied. I think the keywords are also good and represent the description of the content of this research. However, the author(s) failed to highlight the research results, which are in accordance with the research objective, namely "to compare." What is the outline of the comparison?

Authors response:

We have improve the research results:

Results: This study found that the highest perceived benefits and behavioral change come from the non-government spokesperson, of which 26.45% and 18.48% of respondents strongly agree, while the lowest is from a government spokesperson with no medical background. This study also found from five-health spokespersons, the best two are occupied by non-government with medical backgrounds, with 31.52% and 29.35% of respondents strongly agree. However, most respondents had high trust in the governments, with 14.49% strongly agreeing. Compared to those from the governmental sector, spokespersons from the non-governmental sector are perceived to induce higher perceived benefits in delivering the message. However, this does not mean there is no utility in using governmental sector spokespersons, as they are also shown to induce high levels of trust. Overall, governmental and non-governmental spokespersons show utility in different communication aspects, highlighting the need for targeted communication strategies. To conclude, these findings demonstrate that government spokespersons for the COVID-19 pandemic in Indonesia receive the same high level of trust as non-government spokespersons regarding communicating health hazards. The public looks forward to the regularity and routine of the leaders who serve as spokespersons in hopes of easing concerns and tension brought on by the ongoing appearance of the Omicron variation in Indonesia.

2. How does the author(s) determine a representative sample size before carrying out one of the sampling techniques?

Authors response:

Regarding the determination of a representative sample size, we apologize for not providing sufficient clarification in our paper. In our research, we employed a probability sampling technique due to practical constraints and the nature of our study population.
The author first determines the target population to be studied. Because there is already valid data regarding population figures, the sampling technique and the number of samples needed for the study can be determined.

3. This research applies non-probability sampling, so does the Slovin formula work enough to determine the sample size for a study with non-probability sampling?

Authors response:

Probability sampling is used because the population size is known to calculate the required sample size. In determining the respondents are also not limited by specific subjective criteria.
The slovin formula is also appropriate because the slovin formula can be used for the probability sampling method. The slovin technique is a derivative of the Cochran formula and the confidence level is 95% (significance level α=5%).

With a population of 150 million, the required sample size is still 100.

4. Where did the author get the population (150 million)?

Authors response:

The target respondents are social media users as infodemic recipients from spokespersons in educating about the COVID-19 vaccine and health services in Indonesia.

We study it by first mapping the average age of social media users in Indonesia, then collecting data on how many active social media users are in Indonesia. According to several reliable research sources, the number of active social media users in Indonesia in 2019 -2020 is 150 million (Statista, we are social, 2020). Therefore, the population of the study was 150 million people. We employed expert judgment and considered the available resources to determine a feasible sample size that would allow for meaningful analysis and interpretation of the data

5. Why is the margin of error 10%? Is the sample strong enough to produce confident findings?

Authors response:

A 10% margin of error is commonly used for large populations (Regression Analysis, Quantitative Research Methods, Firdaus, 2021). The Slovin formula can be used with the following conditions: e = 0.1 (10%) for a large population, e = 0.02 (20%) for a small population. So the range of samples that can be taken from the Slovin technique is between 10-20% of the study population. Therefore, this study's sample size is appropriate and valid to represent the population. Note: The significance level differs from the margin of error, so the significance level remains low according to the standard (5%).

6. Is this research capable of producing confident results?

Authors response:

- Questionnaire Validity
Before data collection, a pilot study was conducted to test the validity and reliability of the questionnaire. Each questionnaire item was tested using Cronbach's Alpha, the results of which can be seen in Table 2.

- Result Validity
The sampling technique and the number of samples have been determined systematically so that they can represent the population.

Response to reviewer comments No 1 & 4 the abstract section, result & discussion.

Thank you for bringing this important aspect to our attention. Your feedback has been invaluable, and we are committed to incorporating your suggestions to rewrite the abstract, strengthen the introduction and provide a more comprehensive justification for result and discussion section. We will highlight that the findings from such studies can provide valuable insights and evidence-based recommendations for improving communication strategies across diverse health contexts, including but not limited to pandemics.
Competing Interests: No competing interests were disclosed. Close
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Version 2

VERSION 2 PUBLISHED 24 Jan 2023

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Version 2 (revision) 14 Sep 23	read
Version 1 24 Jan 23	read

Hanny Hafiar, Universitas Padjajaran Bandung, Bandung, Indonesia

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28 Sep 2023 | for Version 2

Hanny Hafiar, Faculty of Communication Science, Universitas Padjajaran Bandung, Bandung, Indonesia

1 Views Cite this report Responses(0)

Approved

Thank you for the improvements you have made, so far I think the results of these improvements have met the improvements I recommended. Furthermore, I consider that this article is promising enough to be indexed

Competing Interests

No competing interests were disclosed.

Reviewer Expertise

Health communication; Health promotion

I confirm that I have read this submission and believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard.

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22 Views

14 Jun 2023 | for Version 1

Hanny Hafiar, Faculty of Communication Science, Universitas Padjajaran Bandung, Bandung, Indonesia

22 Views Cite this report Responses(1)

Approved With Reservations

I commend the authors for their efforts. I provide my comments for this article as follows:

The abstract section has briefly justified the purpose of this research well, how the research method is applied. I think the keywords are also good and represent the description of the content of this research. However, the author(s) failed to highlight the research results, which are in accordance with the research objective, namely "to compare." What is the outline of the comparison?
The Introduction section is well-written in the present research context. However, this introductory section does not explain in detail why there is a need for this comparative research. What is the urgency why these health communicators should be compared? Researchers tend to emphasize the importance of risk communication only in the context of a pandemic.
The method is still problematic. How does the author(s) determine a representative sample size before carrying out one of the sampling techniques? It seems this research applies non-probability sampling, so does the Slovin formula work enough to determine the sample size for a study with non-probability sampling? Where did the author get the population (150 million)? And why is the margin of error 10%? Is the sample strong enough to produce confident findings? Is this research capable of producing confident results? It seems unclear. The author(s) need to clarify it.
The results section looks fine. However, in the discussion section, the authors seem to have lacked elaboration on the research findings with the literature studies conducted. It makes the manuscript unbalanced between the literature review that underlies this study and the discussion of its findings. The author(s) need to comprehensively discuss the results and what are the implications of these findings.
This article is quite promising, but the author needs to clarify things that are questionable by reviewers or even readers later.

Is the work clearly and accurately presented and does it cite the current literature?

Yes
Is the study design appropriate and is the work technically sound?

Partly
Are sufficient details of methods and analysis provided to allow replication by others?

Partly
If applicable, is the statistical analysis and its interpretation appropriate?

Partly
Are all the source data underlying the results available to ensure full reproducibility?

Yes
Are the conclusions drawn adequately supported by the results?

Yes

Competing Interests

No competing interests were disclosed.

Reviewer Expertise

Health communication; Health promotion

Respond to this report

Responses (1)

Author Response

14 Sep 2023

Neneng Nurlaela Arief, School of Business and Management, Institut Teknologi Bandung, Bandung, 40132, Indonesia

1. The abstract section has briefly justified the purpose of this research well, how the research method is applied. I think the keywords are also good and represent the description of the content of this research. However, the author(s) failed to highlight the research results, which are in accordance with the research objective, namely "to compare." What is the outline of the comparison?

Authors response:

We have improve the research results:

Results: This study found that the highest perceived benefits and behavioral change come from the non-government spokesperson, of which 26.45% and 18.48% of respondents strongly agree, while the lowest is from a government spokesperson with no medical background. This study also found from five-health spokespersons, the best two are occupied by non-government with medical backgrounds, with 31.52% and 29.35% of respondents strongly agree. However, most respondents had high trust in the governments, with 14.49% strongly agreeing. Compared to those from the governmental sector, spokespersons from the non-governmental sector are perceived to induce higher perceived benefits in delivering the message. However, this does not mean there is no utility in using governmental sector spokespersons, as they are also shown to induce high levels of trust. Overall, governmental and non-governmental spokespersons show utility in different communication aspects, highlighting the need for targeted communication strategies. To conclude, these findings demonstrate that government spokespersons for the COVID-19 pandemic in Indonesia receive the same high level of trust as non-government spokespersons regarding communicating health hazards. The public looks forward to the regularity and routine of the leaders who serve as spokespersons in hopes of easing concerns and tension brought on by the ongoing appearance of the Omicron variation in Indonesia.

2. How does the author(s) determine a representative sample size before carrying out one of the sampling techniques?

Authors response:

Regarding the determination of a representative sample size, we apologize for not providing sufficient clarification in our paper. In our research, we employed a probability sampling technique due to practical constraints and the nature of our study population.
The author first determines the target population to be studied. Because there is already valid data regarding population figures, the sampling technique and the number of samples needed for the study can be determined.

3. This research applies non-probability sampling, so does the Slovin formula work enough to determine the sample size for a study with non-probability sampling?

Authors response:

Probability sampling is used because the population size is known to calculate the required sample size. In determining the respondents are also not limited by specific subjective criteria.
The slovin formula is also appropriate because the slovin formula can be used for the probability sampling method. The slovin technique is a derivative of the Cochran formula and the confidence level is 95% (significance level α=5%).

With a population of 150 million, the required sample size is still 100.

4. Where did the author get the population (150 million)?

Authors response:

The target respondents are social media users as infodemic recipients from spokespersons in educating about the COVID-19 vaccine and health services in Indonesia.

We study it by first mapping the average age of social media users in Indonesia, then collecting data on how many active social media users are in Indonesia. According to several reliable research sources, the number of active social media users in Indonesia in 2019 -2020 is 150 million (Statista, we are social, 2020). Therefore, the population of the study was 150 million people. We employed expert judgment and considered the available resources to determine a feasible sample size that would allow for meaningful analysis and interpretation of the data

5. Why is the margin of error 10%? Is the sample strong enough to produce confident findings?

Authors response:

A 10% margin of error is commonly used for large populations (Regression Analysis, Quantitative Research Methods, Firdaus, 2021). The Slovin formula can be used with the following conditions: e = 0.1 (10%) for a large population, e = 0.02 (20%) for a small population. So the range of samples that can be taken from the Slovin technique is between 10-20% of the study population. Therefore, this study's sample size is appropriate and valid to represent the population. Note: The significance level differs from the margin of error, so the significance level remains low according to the standard (5%).

6. Is this research capable of producing confident results?

Authors response:

- Questionnaire Validity
Before data collection, a pilot study was conducted to test the validity and reliability of the questionnaire. Each questionnaire item was tested using Cronbach's Alpha, the results of which can be seen in Table 2.

- Result Validity
The sampling technique and the number of samples have been determined systematically so that they can represent the population.

Response to reviewer comments No 1 & 4 the abstract section, result & discussion.

Thank you for bringing this important aspect to our attention. Your feedback has been invaluable, and we are committed to incorporating your suggestions to rewrite the abstract, strengthen the introduction and provide a more comprehensive justification for result and discussion section. We will highlight that the findings from such studies can provide valuable insights and evidence-based recommendations for improving communication strategies across diverse health contexts, including but not limited to pandemics.

View more View less

Competing Interests

No competing interests were disclosed.

Alongside their report, reviewers assign a status to the article:

Approved - the paper is scientifically sound in its current form and only minor, if any, improvements are suggested

Approved with reservations - A number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.

Not approved - fundamental flaws in the paper seriously undermine the findings and conclusions

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Comparative analysis of health authorities’ spokespersons and health influencers during the COVID-19 pandemic

Abstract

Keywords

Revised Amendments from Version 1

Introduction

Literature review

Public communication campaign theory

Health risk communication

Risk communication before, during, and after a pandemic

Context of health authorities spokesperson

Comparative research on different spokespersons within a country during a pandemic

Methods

Data collection

Table 1. Respondent summary.

Ethical issues

Data analysis

Table 2. Respondent summary.

Table 3. Spokesperson code.

Results

Perceived benefit

Figure 1. Public Campaign vs Perceived Benefit (PCB) in Indonesia.

Behavioral change

Figure 2. Behavioral Change (BC) in Indonesia.

Vaccination promotion

Figure 3. Vaccination Promotion (VP).

The comparison of health spokesperson

Figure 4. Health Spokesperson Comparation (HS).

The channels

Figure 5. Public Campaign (PC) channel.

Risk and health communication

Figure 6. Risk and Health Communication (RHC) in Indonesia.

Table 4. Risk and health communication.

Trust

Figure 7. Trust Government Spokesperson in Indonesia.

Figure 8. Leadership Communication (LC) consistency.

Figure 9. Leadership Communication (LC) directionally.

Figure 10. Leadership Communication (LC) Trust Leaders in Australia.

Discussion

Conclusions

Limitation and future research

Data availability

Underlying data

Extended data

References

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