Coercive Communication: Compliance with Government Policies to Reduce COVID-19 Spread in Indonesia

Abstract

This article aims to explain the direct and indirect effects of coercive communication on the increase of public compliance with Indonesian government policies to reduce the spread of COVID-19. This study employed a quantitative method. The data were collected for 11 days (29 May–8 June 2020). This research involved 580 respondents who were aged 15 years and over and willingly answered the questionnaire. The research questionnaire was distributed through social media platforms, such as Facebook, WhatsApp group and Instagram. The research data were analysed using statistical path analysis with SEM WarpPLS7.0. The findings indicate that coercive communication significantly and directly affects public compliance with seeking information and performing attitudes to suppress the spread of COVID-19 in Indonesia. Thus, coercive communication can be practically applied as an important alternative strategy in other public policy communications to get a fast response, encourage information seeking and trigger public compliance.

Keywords

Coercive communication information seeking public attitude public compliance COVID-19

Introduction

COVID-19 emerged in Wuhan, China, in December 2019 (Brindha et al., 2020; Leite et al., 2020; Ozili, 2020), and since then it has spread to 223 countries (WHO, 2021). In Indonesia, 1,089,308 people had tested positive and 13,783 people died from COVID-19 between 14 February 2020 and 2 February 2021 (coronatracker, 2021). This fact shows an increase in COVID-19 positive cases and slightly indicates that the number of people infected with COVID-19 will decrease soon. The government of Indonesia issued some policies to respond to the increasing COVID-19 positive cases. One of the policies is the Large-scale Social Restriction stipulated on 31 March 2020. This policy was applied in the form of (a) school and office closures, (b) religious event restriction, (c) event restriction in public facilities or areas, (d) social and cultural event restriction and (e) transportation mode restriction. This policy was implemented in Jakarta and lasted for 14 days in the first phase and for 14 days in the second phase from 14 to 27 September 2020. Customers were also restricted to use an online ride-hailing taxi. Since the economic situation became difficult, the government distributed food valued at IDR200,000 to families in Jakarta, Bogor, Depok, Tangerang and Bekasi. This food distribution was conducted for three months.

Public responses to the government policies were polarised. The proponents of these policies obeyed performing them; on the other hand, the opponents showed negative attitudes and behaviour by ignoring these policies (Azlan et al., 2020). It is considered normal that some people oppose the policies because they have individual experiences, references and understandings of these policies (Banton, 2011). Therefore, it is necessary to find a solution to decrease the number of opponents of the policies. However, this effort is not simple, takes time and requires the right and effective approach and communication techniques (Cancela et al., 2016; Clarke, 1999).

To date, literature on communication and COVID-19 has increasingly been published. The perspectives of communication science regarding these issues include the phenomenology studies on social media (Brindha et al., 2020), the role of social media during the COVID-19 pandemic (Hussain, 2020), effective communication as COVID-19 cure (Dhoot, 2020; Singhal & Kim, 2021), social media and public opinion (Han et al., 2020), risk communication (Lim & Nakazato, 2020) and other articles that focus on COVID-19 from diverse disciplines and using various approaches. However, only a few studies have investigated the role of information sources, coercive communication, knowledge and attitude to obey COVID-19 policies and raise awareness of COVID-19.

COVID-19 cases in Indonesia increased every day. The regional and national governments issued policies and regulations to battle the COVID-19 spread, but there was no significant effect on slowing down the COVID-19 cases. Jakarta’s authority would have penalised people if they had disobeyed the policies. The fine was IDR100,000 up to 250,000. Unfortunately, this penalty could not slow down the COVID-19 spread in Indonesia.

This study aims to reveal strategies from communication science perspectives to build public awareness and obedience to slow down the COVID-19 spread. Obedience refers to society’s acceptance of policies, such as social and physical distancing, Large Scale Social Restriction, and work from home, to lower the COVID-19 infection. The obedience also suggests some tips and communication theories explaining and mitigating the public resistance to COVID-19 policies. This study contributes to the government’s efforts to implement communication approaches and build public obedience. Unfortunately, building public obedience is complex because it accumulates some strategies, including accurate communication strategies.

Literature Review

Coercive Communication and Information Seeking

There are several reasons why humans speak, listen, read and write; one of the reasons is seeking information to fulfil humans’ needs. These needs include physical, social and psychological needs, such as maintaining social relations (DeVito, 2012) and seeking pleasure, affection and health (Adler & Rodman, 2006a).

Information seeking is a complex process consisting of social, communicative and interactive behaviour to fulfil goals and respond to specific needs (Ikoja-Odongo & Mostert, 2006). Since information seeking is a social behaviour and an act of communication, it involves other parties. Information-seeking occurs due to compliance with the pressure or coercion from certain parties, such as the authorities or the government, to comply with a policy that someone does not like (Myers & Twenge, 2016). Information seeking is a result of pressure or coercion of certain parties and is called coercive communication. Thus, information seeking, attitude changes and compliance can be influenced by persuasive communication (Al-Marshoudi et al., 2021; Perloff, 2003; Singhal & Kim, 2021) and coercive communication (Mani, 2017).

Coercive communication is frequently associated with persuasive communication. These two types of communication are communication strategies to change the audience’s awareness and behaviour (Galle et al., 2021). However, the definitions of coercive and persuasive communications are different. Coercive communication is derived from the Latin word ‘arcere’ which is the root of the word ‘incarceration’ which means to close or hold back (Powers, 2007). The word coercion in English means restraint. This concept explicitly shows that the coercive approach implies the use of threats, sanctions, intimidation, coercion and anxiety to change the audience’s cognition, affection and behaviour (Mani & Guntoro, 2020; Powers, 2007; Sjostrom, 2006). Persuasive communication refers to the process of influencing, inviting or motivating people to take certain attitudes or actions voluntarily, without being coerced in accordance with the communicator’s goals (Adler & Rodman, 2006b; DeVito, 2017; Perloff, 2003). For example, inviting others to donate to the homeless, quitting smoking, throwing trash in the space provided and so on.

Several previous studies have explained the effectiveness of coercive communication in changing the audience’s behaviour. Several studies investigated public policy communication and have found that coercive communication affects public compliance (Mani, 2017; Sjostrom, 2006). Meanwhile, research conducted examined the problems of alcohol control in Switzerland and has discovered that coercive instruments are not related to the problems of alcohol control (Sager, 2009).

Previous studies have shown different results regarding the effect of coercive communication, so this is tested further in the context of implementing policies for the COVID-19 control programme in Indonesia. This study is guided by the following hypotheses.

H₁: Coercive communication affects information seeking about controlling the spread of COVID-19.

H₂: Coercive communication affects public attitude towards controlling the spread of COVID-19.

H₃: Coercive communication affects public compliance with controlling the spread of COVID-19.

Information Seeking and Public Attitude

Information seeking is broadly defined as a user’s action to find information needs, information retrieval and subsequent use (Ikoja-Odongo & Mostert, 2006). People sought information about COVID-19 because the number of people infected with the COVID-19 virus increased. Thus, they were encouraged to seek knowledge from various social media platforms to fight or avoid the virus transmission (Liu, 2020; Rayani et al., 2021).

A person experiences a change in knowledge because they receive information from the surrounding environment. Such a phenomenon is explained in the field theory by Kurt Lewin (1943) who postulates that the environment can stimulate changes in human behaviour (Roşca, 2020). The communication environment is defined as physical, time and socio-cultural contexts and sources of information gained by a person (DeVito, 2017).

The audience’s behaviour in communicating and using the media is driven by their needs. These needs aim to obtain information and increase their knowledge about environmental issues (Adler & Rodman, 2006b; DeVito, 2017; Schramm & Roberts, 1971; Vivian, 2008).

The motives and factors that encourage audiences to seek information are explained in the theory of uses and gratification. This theory is based on the assumption that the audience actively uses media for certain purposes and chooses information according to their needs (West & Turner, 2018), such as physical, identity, social, or practical needs (Adler & Rodman, 2006b).

Nowadays, the public widely access information from communication media on the internet, such as social media (DeVito, 2017; Liu, 2020; Rayani et al., 2021) that provides various information. Unfortunately, not all information about COVID-19 on social media is valid (Ali et al., 2020). This means that social media can also become a source of misinformation and myths about the COVID-19 vaccine (Kricorian et al., 2022; Roozenbeek et al., 2020). Misinformation on social media sometimes spreads faster than the COVID-19 virus (Sahni & Sharma, 2020).

Misinformation and myths are widely accepted by people who have low levels of education and income and live in rural areas (Kricorian et al., 2022). In addition, it is difficult to distinguish between true and fake news on social media because everyone can post information on it. Therefore, COVID-19 information urgently involves competent institutions or individuals, such as doctors, who act as main communicators to reduce uncertain truths of social media news (Garett & Young, 2021). Social media plays a quite significant role, and hence media literacy is needed to prevent vague and unreliable sources of information (Hobbs, 2011).

The first consequence of exposure to a message or persuasion is a change in knowledge that enables a person to experience a change in mind from not knowing to knowing and from not understanding to understanding (Donohue et al., 1973). After experiencing a change in knowledge, a person will develop a change in attitude (Cancela et al., 2016) and behaviour (Clark, 1999).

H₄: Information seeking affects public attitude.

H₅: Information seeking affects public compliance.

Attitude and Public Compliance

The field theory explains that a person’s attitude changes due to externally received stimuli or messages (Roşca, 2020). This means that attitude changes occur as an effect of communication or social interaction.

Attitudes are defined as beliefs and feelings of a person or an event. For example, a person likes coffee, acts positively towards his neighbours, respects other groups to prevent discrimination, supports policies and accepts these policies. Attitude has three components: affection (feelings), behavioural tendency and cognition (thoughts) (Myers & Twenge, 2016).

Communication and compliance are closely related, where in the perspective of communication, compliance is the effect of a communication process. This is relevant to Lasswell’s formula, namely ‘who says, what in which channel, to whom, and with what effects’. This formula clearly states the elements of linear communication, which include communicators, messages, media, receivers and effects (Hardt, 2008). The linear communication model describes a communication process that ends with effects. These effects suggest changes in cognition, affection, psychomotor, or behaviour of communicants or target audiences (DeVito, 2017).

Compliance is an attitude that occurs in a person as a result of the communication process, either through informative, persuasive or coercive communication (Burgoon et al., 1987). Compliance can be categorised as a change in a person’s behaviour after receiving a message from the environment. In Field Theory by Kurt Lewin, a person’s behaviour is a ‘personal and environmental function’ (Burnes, 2004; Roşca, 2020). Changes in behaviour that occur within a person are not only caused by the framework of his knowledge and experience, but are also caused by environmental pressures (Burnes & Cooke, 2012).

Most of the time, compliance is related to an individual reaction to norms and regulations in social and environmental contexts. Compliance is conceptualised as individual behaviour towards external forces or stimuli from legal instruments, economic sanctions and normative beliefs (Hou et al., 2011). Compliance has several causes, and one of them is sources of authority, such as the government (Branscombe & Baron, 2017).

According to the aforementioned explanation, one of the causes of compliance is authority. For example, the government issues policies to pay taxes, and the public participates in vaccine or immunisation programmes. Several previous studies have discovered that attitude positively affects compliance (Alabede et al., 2011; Javier et al., 2021; Yanti et al., 2020).

H₆: Public attitude affects public compliance.

Figure 1 shows that public compliance can be influenced directly and indirectly by coercive communication (Cr) through information seeking (Si) and public attitude (Pa). Based on this research framework, direct and indirect effects is evidence in line with previous literature that coercive communication (Mani & Guntoro, 2020; Sager, 2009), information seeking (Singhal & Kim, 2021) and public attitude affect compliance (Alabede et al., 2011).

Figure 1.

Source: Output WarpPLS. 7.0.0

Methods

This research aims to contribute to social sciences, specifically communication science. However, the results of this research can be utilised in the fields of communication, public administration, public health communication and community development.

Philosophically, this research is based on a postpositivist worldview that emphasises causative determinism. The research problems for post-positivism reflect the need to identify factors that influence the final outcome and quantitative research. Based on the postpositivist worldview, this research employed a quantitative method (Creswell, 2016).

This study aims to determine factors that directly and indirectly influence public compliance with the Indonesian government policy against the spread of COVID-19. The data of this research were derived from Indonesians aged 15 years old. The questionnaire was distributed for 11 days from 29 May to 8 June 2020. This research involved 508 respondents who were asked to voluntarily answer questions on the online questionnaire via social media, such as Facebook and WhatsApp groups.

The research hypotheses were tested using the structural equation model (SEM) with WarpPLS 7.0 to prove the strengths and weaknesses of the direct and indirect effects of all research variables (Kock, 2020; Sholihin & Ratmono, 2021).

Results

Frequency Distribution

The data on the education level of the respondents show that the respondents earned high school education (11.72%), diploma or bachelor’s degree (58.28%), master’s degree (25.17%), and doctoral degree (4.83%). Meanwhile, the data on employment indicate civil servants (37.41%), students (13.62%), employees (21.38%), housewives (3.62%), jobseekers (3.97%), social workers/art workers (1.03%), entrepreneurs (18.62%) and farmers (0.34%).

This research has discovered that the public’s initial or basic knowledge defines COVID-19 as a fast-spreading virus originating from Wuhan, China. This definition indicates that their basic knowledge about the COVID-19 virus is very low. Thus, intensive socialisation and campaigns are necessary to improve public knowledge about COVID-19. Moreover, only a few studies state that COVID-19 is a deadly virus. Therefore, the result shows that the public fear of COVID-19 is very low. A low level of fear will result in the inattention of policies, such as social or physical distancing, large-scale social restrictions, stay at home and work from home.

The public has learned about COVID-19 from various sources, such as government reports, mass media and social media. In Indonesia, the report communicator is affiliated with the authority of the national government. Then, the regencies or municipalities broadly interpret the report by considering the conditions and needs of their respective regions.

In Indonesia, official policies are coordinated by the national, regional/regency, sub-district and sub-district/village governments. Some sources of information most widely used by the public to find information about COVID-19 are summarised in Table 1.

Table 1 shows that the public has various sources of information from the government, friends, family, mass media and digital media. They widely access information about COVID-19 from various sources, such as online news media (75.86%), social media (75.51%), television (55.34%) and the government (37.76%). This finding shows that the main source for Indonesians to get information about COVID-19 is personally accessed media. Thus, their choice of information is under personal control. The public watches television as the main source to find information because television is the main channel of the government, especially the Ministry of Health of the Republic of Indonesia, to inform COVID-19 conditions. In other words, television is the media to seek information and makes people an agent to socialise public health issues (Uznienė, 2012).

Furthermore, Table 1 describes that the government is the fourth source of public information about COVID-19, but the category is low as seen from the intensity of the government’s direct communication with the community. In fact, the government prefers using social media and mass media which prevents people from mass gathering. Thus, the Indonesian government is basically the main communicator or source of conveying all policies and information about COVID-19.

Table 1.

Sources of Information Widely Accessed by the Public to Find Information About COVID-19.

Public Sources of Information	Frequency	Percentage	Category
Government	219	37.76	Low
Friend	136	23.45	Low
Neighbour	43	7.41	Very low
Family	129	22.24	Low
Television	321	55.34	Average
Radio	48	8.28	Very low
Newspaper	62	10.69	Very low
Online news media	440	75.86	High
Social media (Facebook, WhatsApp, YouTube, Instagram)	438	75.51	High

Source: Primary data in 2021.

The public has multiple media choices to find information about COVID-19 because they have different trust in existing media (Håkansson & Witmer, 2015; Sherchan et al., 2013). Table 2 presents Indonesians’ levels of trust in information sources to find information about COVID-19.

Table 2.

Indonesians’ Preference for Sources of Trusted Information to Find Information About COVID-19.

Sources of Information Followed	Frequency	Percentage	Category
Government	225	38.79	Low
Friends	6	1.03	Very low
Neighbours	1	0.17	Very low
Family	13	2.24	Very low
Television	104	17.93	Very low
Radio	3	0.51	Very low
Newspapers	9	1.55	Very low
Online news media	115	19.83	Very low
Social media (Facebook, WhatsApp, YouTube,and Instagram)	87	15	Very low

Source: Primary data in 2021.

Table 2 shows that all sources of information about COVID-19 policies still receive a low level of trust from the public. Although the public widely accesses mass media (television), online news media and social media, they still cannot trust these media. This finding interprets that social media, online news media and television are less trusted sources of information about COVID-19. Therefore, the government must use a direct communication approach with the public. Direct communication could reduce personal and social distances between the government and the public and allows the public to confirm not understandable messages (Mani & Guntoro, 2020).

Table 2 also shows that the public is more likely to trust information from the government (38.79%), but this trust is categorised as low because it is below 50%. This finding denotes that although the government controls all information about COVID-19, their information sources receive low trust from the public.

The theory of uses and gratification postulates that the audience actively finds information from the media and has a motive for this action. Their active searching for information depends on their wishes (Hussain et al., 2020; Kamboj, 2020; Lev-On, 2011). One of the motives for accessing the media is to look for information that suits their needs. The public’s needs for information are summarised in Table 3.

Table 3 shows that the public realises the importance of knowing the information about COVID-19 as indicated by the fact that the entire categories are mostly at a moderate level. This phenomenon means that the public’s need for information about COVID-19 is quite low. Moreover, this phenomenon implies that their worry and fear of COVID-19 are low. Low levels of need, worry and fear more significantly encourage the public to violate the policy. Therefore, it is necessary to examine the influence of information sources (online news media and social media), coercive communication, knowledge and affection to communicate the COVID-19 policies on public behaviour.

Table 3.

Most Needed Information on COVID-19.

Most Needed Information	Frequency	Percentage	Category
Characteristics/symptoms of COVID-19	308	53.10	Average
Transmission of COVID-19	258	44.48	Average
Cure/drug for COVID-19	249	42.93	Average
Self-protection from COVID-19	389	67.07	High
Areas of COVID-19 spread	354	61.03	High

Source: Primary data in 2021.

The Instrument Validity

The validity explains that the measurement instrument (questionnaire) is appropriate to test the research variables. The research instrument is considered valid if the p value is less than .05.

Table 4 shows the WarpPLS 7.0 outputs. All measurement instruments (questionnaires) are declared valid because all question items have loading values greater than 0.70 and a significance of 0.001 or less than 0.05.

Table 4.

Output Combined Loadings and Cross-loadings.

	Si	Cr	Pa	Pc	Type (as defined)	SE	P Value
si1	0.867	–0.035	–0.004	0.037	Reflect	0.038	<.001
s12	0.867	0.035	0.004	–0.037	Reflect	0.038	<.001
cr1	0.065	0.808	0.324	–0.232	Reflect	0.038	<.001
cr2	–0.014	0.862	0.226	–0.040	Reflect	0.038	<.001
cr3	–0.047	0.752	–0.329	0.275	Reflect	0.038	<.001
cr4	–0.007	0.731	–0.286	0.021	Reflect	0.038	<.001
pa1	0.108	0.139	0.600	–0.494	Reflect	0.039	<.001
pa2	0.034	0.244	0.687	–0.405	Reflect	0.038	<.001
pa3	0.095	0.163	0.628	–0.442	Reflect	0.039	<.001
pa4	0.055	0.662	–0.374	0.150	Reflect	0.040	<.001
pa5	0.118	0.494	–0.416	0.224	Reflect	0.040	<.001
pa6	0.156	0.461	–0.365	0.360	Reflect	0.040	<.001
pa7	–0.018	0.264	0.751	0.444	Reflect	0.038	<.001
pa8	–0.017	0.099	0.833	0.380	Reflect	0.038	<.001
pa9	0.008	–0.018	0.815	0.593	Reflect	0.038	<.001
pc1	–0.079	0.046	0.241	0.881	Reflect	0.038	<.001
pc2	0.083	–0.163	–0.026	0.870	Reflect	0.038	<.001
pc3	–0.003	0.119	–0.223	0.852	Reflect	0.038	<.001

Source: Output WarpPLS. 7.0.

Notes: Loadings are unrotated and cross-loadings are oblique-rotated.

SEs and p values are for loadings.

p values < .05 are desirable for reflective indicators.

Table 5 shows that the R² of variable Si (information seeking) is 0.932. This denotes that Si (information seeking) can be explained with 6.8% by the variance of Cr (coercive communication). Furthermore, variable Pa (public attitude) is 0.474 indicating that Pa can be explained with 52.7% by the variance of Cr and Si. Meanwhile, the Pc (public compliance) variable is 0.437 indicating that Pc can be explained with 56.5% by the variance of Cr, Si, and Pa. The R² results assume that the Pc variable is positively influenced by the variance of Cr, Si and Pa constructs.

Table 5 shows Q² values that detail prediction levels of the accurate use of the model in real terms in the field. The accurate variables Cr to Si are 0.070, the variables Cr and Si to Pa are 0.527, and the prediction accuracy of variables Cr, Si, and Pa to Pc is 0.566. The estimation results of all variables show good-predictive accuracy because the value is above zero.

Table 5.

Outputs of Latent Variable Coefficient.

	Si	Cr	Pa	Pc
R ²	0.069		0.527	0.565
Adj. R²	0.068		0.526	0.563
Composite reliable	0.858	0.869	0.649	0.902
Cronbach’s alpha	0.670	0.798	0.621	0.836
Avg. var. extracted	0.752	0.624	0.399	0.753
Full-collinearity VIFs	1.127	2.125	2.724	2.277
Q ²	0.070		0.527	0.566
(No. diff. vals.)	16.000	86.000	362.000	38.000
(No. diff. vals./N)	0.028	0.148	0.624	0.066
Min	–1.777	–3.805	–3.820	–3.215
Max	1.725	0.892	1.358	0.934
Median	–0.030	0.250	0.275	0.248
Mode	–0.610	0.892	0.928	0.934
Skewness	0.111	–1.473	–1.209	–0.895
Exc. kurtosis	–0.795	1.991	1.321	0.059
Unimodal-RS	Yes	Yes	Yes	Yes
Unimodal-KMV	Yes	Yes	Yes	Yes
Normal-JB	No	No	No	No
Normal-RJB	No	No	No	No
Histogram	View	View	View	View

Source: Output WarpPLS. 7.0.

Notes: RS = Rohatgi–Székely (top); KMV = Klaassen−Mokveld−van Es (bottom); JB = Jarque–Bera (top); RJB = robust Jarque–Bera (bottom).

Description of the Hypothesis Test

The WarpPLS 7.0 outputs show that all the appropriate fit model criteria have met the requirements with an average path coefficient of 0.321, an average R² of 0.387 and a p value of less than .001. The average full-collinearity VIF value is 2.063 < 5. Meanwhile, the Tenenhaus GoF value is 0.495, including the explanatory power category on the large criterion. Sympson’s paradox ratio value is 1, indicating that it is free from Sympson’s paradox.

Direct Effects

The direct effects of variables shows that Cr has an effect on Si with a coefficient value of 0.263 (p < 0.01), on Pa with a coefficient value of 0.677 (p < 0.01) and on Pc with a coefficient value of 0.225 (p < 0 0.01). Meanwhile, Si has an effect on Pa with a coefficient value of 0.135 (p < 0.01) and on Pc with a coefficient value of 0.077 (p < 0.03). Pa has an effect on Pc with a coefficient value of 0.547 (p < 0, 01). The direct effects of variables are significant because all p values are below .05 (Figure 2). Thus, all hypotheses are accepted, meaning that all variables influence other variables directly. Therefore, the coercive communication carried out by the Indonesian government can encourage the public to seek information to increase their knowledge. This knowledge promotes public compliance with the government policies.

Figure 2.

Source: Output WarpPLS. 7.0.

Indirect Effects

Table 6 explains the indirect influence of the Indonesian government’s policy on Pc to reduce the spread of COVID-19.

Table 6.

Indirect Effects.

Indirect Effects for Paths with Two Segments
	Si	Cr	Pa	Pc
Pa		0.036
Pc	0.074	0.391
Number of Paths with Two Segments
	Si	Cr	Pa	Pc
Pa		1
Pc	1	2
P values of Indirect Effects for Paths with Two Segments
	Si	Cr	Pa	Pc
Pa		0.112
Pc	0.006	<0.001

Source: Output WarpPLS. 7.0.

The indirect effect of Cr to Si on Pa is 0.036 with a p value of .112 (not significant). Moreover, the indirect effect of Cr on Pc to Pa is 0.391 with a p value < .001 (significant). Meanwhile, the indirect effect of Si on Pc to Pa is 0.074 with a p value of .006 (significant).

Coercive communication has three indirect effects:

Coercive communication increases public knowledge through information seeking. Coercive communication or instructions from the government is not mediated by information seeking because information seeking ideally increases public knowledge of the Indonesian government’s policies to reduce the spread of COVID-19.

Public compliance will be achieved if the government forced the public to be aware of the policy. This reality shows that a group of people will obey and willingly accept the policy when they are pressured by the government.

Clear information results in public compliance and awareness of the policy.

Discussion

The results of the SEM-PLS test show that some of the research results are unique and explainable. The uniqueness refers to SEM-PLS’s ability to explain the direct and indirect effects of variables simultaneously (Kock, 2020; Sholihin & Ratmono, 2021).

The initial discussion of the research findings is the society’s sources of messages to access information about the COVID-19 vaccine programme. Some sources widely accessed by people to find information are online news portals and social media. The statistical growth of Indonesia’s internet users in January 2021 was promising because it reached 202.6 million people, and social media users reached 170 million people; this number increased by 10 million people in a year (Kemp, 2021).

H₁ states that coercive communication has little effect on encouraging someone to seek information about government policies or COVID-19 with a path coefficient value of 0.263. This finding assumes that coercive communication cannot be used as the main approach to encourage the public to seek information about the government policies. Coercive communication less effectively builds the public desire to find the necessary information.

Meanwhile, the second hypothesis (H₂) predicts that coercive communication greatly influences public attitudes with a path coefficient value of 0.677. This number signifies that the public attitudes will change easily if the government pressures them to firmly apply the policy. However, other studies have found that coercive communication through threats or punishment leads to policy avoidance (Mohdali et al., 2014).

The result of H₃ shows that coercive communication has an influence on public compliance, of which the path coefficient is 0.225. This indicates that public compliance increases when the government uses a coercive approach.

As predicted in fourth hypothesis (H₄), the information seeking (Si) can encourage changes in public attitude (Pa). However, the results of statistical tests show that private information seeking has a very small effect on public attitudes with a path coefficient of 0.135. This finding can be interpreted that an independent search for information through online news media and social media insignificantly contributes to changes in public attitudes. Although the contribution is small, online news media and social media still play a role in creating public knowledge and attitudes (Ndumbe-Eyoh & Mazzucco, 2016; Paek & Hove, 2021; Torres et al., 2021) as well as changing their attitudes and behaviour (Nasir, 2013; Pentina & Tarafdar, 2014; Saunders & Goddard, 2002). Thus, online news media and social media have not become the main media or channels to create public compliance with the government policies to reduce the spread of COVID-19. Therefore, the Indonesian government needs other media to create public compliance with the COVID-19 policies.

This study has discovered that information seeking influences public compliance of which a path coefficient value is 0.07. This finding supports the fifth hypothesis (H₅) and indicates that public compliance with the government policies of reducing COVID-19 is insignificantly influenced by personal information seeking on online news media and social media. Thus, independent information seeking has a weak effect on public compliance with the government policies.

H₆ predicts that the public attitude has a major influence on public compliance of which a path coefficient is 0.547. This number denotes that public compliance is well-formed when it is based on the public’s knowledge, awareness and positive attitudes. Public shows a positive attitude due to the great benefits of obeying a rule. The obedience theory assumes that humans are rational beings and will consider the benefits if they are obedient (Albarracín et al., 2003; Meier & Morgan, 1982).

An interesting finding of this study shows that coercive communication has a significant direct effect on public knowledge, attitude and public compliance. It means that the government’s pressure or coercion makes the public understand, accept and comply with the government policies of COVID-19. This finding is relevant to the results of a previous study that coercive strategies have a direct effect on compliance with cooperation (Hausman & Johnston, 2010). In other contexts, coercive communication represented by the power of authority or government correlates with compliance, for example, compliance with paying taxes (Kastlunger et al., 2013). However, the consequence of using coercive communication or authority power is policy avoidance (Kastlunger et al., 2013; Mohdali et al., 2014). This statement denotes that coercive communication can only lead to pseudo-compliance, psychological pressure and fear (Powers, 2007), but these effects do not last long. Thus, coercive communication can be categorised as an ineffective form of communication (Dev et al., 2011) so that it cannot be used as the main communication approach. Therefore, to create effective communication, several other communication approaches, such as informative, persuasive and educative approaches, should be included (Chan-Olmsted & Chang, 2016).

Conclusion

Internet and social media could become a source of knowledge to change people’s attitudes and behaviour. However, online news media and social media have a low influence on increasing public knowledge and attitudes towards the Indonesian government’s policy on COVID-19. This condition signifies that personal information seeking through online news media and social media insignificantly contributes to people’s attitude and behaviour changes. This reality shows that the use of online news media and social media by the government less effectively increases public knowledge, awareness and compliance.

Basically, most social media users and online news readers have portrayed the diverse demography in Indonesia. For information seeking of the government policies on COVID-19, this study shows the low contribution of social media and people’s activity online searching for the news. Several previous studies have represented a broader social media use in Indonesia as an information source for political learning (Intyaswati et al., 2021) and social media influences on democratisation processes (Gazali, 2014). Social media, however, continues to serve as a source of information and entertainment for the country’s media nuance.

Coercive communication is one of the communication strategies that package messages in the form of coercion, threats and even punishment for those who ignore or violate the messages. Coercive communication can be used as the last strategy when all communication methods have failed to create an effect for the audience or the public.

The conceptual boundaries of coercive communication are relevant to the research findings on the implementation of Indonesian government policies of COVID-19. Coercive communication has a significant direct effect on attitude and public compliance, but it indirectly affects public compliance through information seeking and public attitude. Therefore, coercive communication highly contributes to create public compliance with the COVID-19 policy in Indonesia. Therefore, the government, public figures and policy communicators can use a coercive approach to disseminate policy products and create public awareness and compliance. However, the implementation of coercive communication must consider human values.

The novelty of this research is to prove and find out that coercive communication variables have a real influence on creating knowledge, positive attitudes and public compliance with COVID-19 policies. To date, only a few studies have used and proved coercive communication variables, especially in public policy communication. Therefore, coercive communication can be an important variable investigated by social research in the future, especially to create effective communication in various contexts.

Footnotes

Declaration of Conflicting Interests

The authors declare no potential conflicts of interest with respect to the research, authorship and/or publication of this article.

Funding

The authors received no financial support for the research, authorship and/or publication of this article.

References

Adler

R. B.

, & Rodman

(2006a). Understanding human communication. Oxford University Press.

Adler

R. B.

, & Rodman

(2006b). Understanding human communication (9th ed.). Oxford University Press.

Alabede

J. O.

, Ariffin

Z. Z.

, & Idris

K. M.

(2011). Individual taxpayers’ attitude and compliance behaviour in Nigeria: The moderating role of financial condition and risk preference. Journal of Accounting and Taxation, 3(5), 14. http://www.academicjournals.org/JAT

Albarracín

, McNatt

P. S.

, Klein

C. T. F.

, Ho

R. M.

, Mitchell

A. L.

, & Kumkale

G. T.

(2003). Persuasive communications to change actions: An analysis of behavioral and cognitive impact in HIV prevention. Health Psychology, 22(2), 166–177. 10.1037/0278-6133.22.2.166

Ali

S. H.

, Foreman

, Tozan

, Capasso

, & Jones

Abbey M.

, D

R. J.

. (2020). Trends and predictors of COVID-19 information sources and their relationship with knowledge and beliefs related to the pandemic: A nationwide cross-sectional study. JMIR Public Health and Surveillance. 10.2196/preprints.21071

Al-Marshoudi

, Al-Balushi

, Al-Wahaibi

, Al-Khalili

, Al-Maani

, Al-Farsi

, Al-Jahwari

, Al-Habsi

, Al-Shaibi

, Al-Msharfi

, Al-Ismaili

, Al-Buloshi

, Al-Rawahi

, Al-Barwani

, & Al-Abri

(2021). Knowledge, attitudes, and practices (KAP) toward the COVID-19 vaccine in Oman: A pre-campaign cross-sectional study. Vaccines (Basel), 9(6). 10.3390/vaccines9060602

Azlan

A. A.

, Hamzah

M. R.

, Sern

J., Ayub

S. H.

, & Mohamad

(2020). Public knowledge, attitudes and practices towards COVID-19: A cross-sectional study in Malaysia. PLoS One, 15(5), e0233668. 10.1371/journal.pone.0233668

Banton

(2011). A theory of social categories. Sociology, 45(2), 15. 10.1177/0038038510394013

Branscombe

N. R.

, & Baron

R. A.

(2017). Social psychology (14th ed.). Pearson Education.

10.

Brindha

, Jayaseelan

, & Kadeswara

(2020). Social media reigned by information or misinformation about COVID-19: A phenomenological study. Social Sciences & Humanities Open. 10.2139/ssrn.3596058

11.

Burgoon

J. K.

, Pfau

, Parrott

, Birk

, Coker

, & Burgoon

(1987). Relational communication, satisfaction, compliance-gaining strategies, and compliance in communication between physicians and patients. Communication Monographs, 54. 10.1080/03637758709390235

12.

Burnes

(2004). Kurt Lewin and the planned approach to change: A re-appraisal. Journal of Management Studies, 41(6), 977–1002.

13.

Burnes

, & Cooke

(2012). Kurt Lewin’s field theory: A review and re-evaluation. International Journal of Management Reviews, 15(4). 10.1111/j.1468-2370.2012.00348.x

14.

Cancela

, Requero

, Santos

, Stavraki

, & Briñol

(2016). Attitudes toward health-messages: The link between perceived attention and subjective strength. European Review of Applied Psychology, 66(2), 57–64. 10.1016/j.erap.2016.02.002

15.

Chan-Olmsted

S. M.

, & Chang

B.-H.

(2016). Audience knowledge, perceptions and factors affecting the adoption intent of terrestrial digital television. New Media & Society, 8(5), 773–800. 10.1177/1461444806067588

16.

Clarke

(1999). Changing attitudes through persuasive communication. Nursing Standard, 13(30), 45–47.

17.

coronatracker. (2021). Corona Tracker. https://www.coronatracker.com/country/indonesia/

18.

Creswell

J. W.

(2016). Research design : Qualitative, quantitative, and mixed methods approaches (3rd ed.). Sage Publications.

19.

Dev

C. S.

, Grzeskowiak

, & Brown

J. R.

(2011). Opportunism in brand partnerships. Cornell Hospitality Quarterly, 52(4), 377–387. 10.1177/1938965510397656

20.

DeVito

J. A.

(2012). Human communication: The basic course. Pearson Education, Inc.

21.

DeVito

J. A.

(2017). Human communication: The basic course (12th ed.). Pearson Education, Inc.

22.

Dhoot

(2020). Effective communication approaches works as medicine to safeguard life on earth: A study in concern with novel corona virus (COVID-19). Journal of Content, Community and Communication, 11(10), 285–294. 10.31620/jccc.06.20/22

23.

Donohue

G. A.

, Tichenor

P. J.

, & Olien

C. N.

(1973). Mass media functions, knowledge and social control. Journalism Quarterly. Journalism Quarterly, 50(4), 652–659.

24.

Galle

, Sabella

E. A.

, Roma

, De

Giglio, O.

, Caggiano

, Tafuri

, Da

Molin, G.

, Ferracuti

, Montagna

M. T.

, Liguori

, Orsi

G. B.

, & Napoli

(2021). Knowledge and acceptance of COVID-19 vaccination among undergraduate students from Central and Southern Italy. Vaccines (Basel), 9(6). 10.3390/vaccines9060638

25.

Garett

, & Young

S. D.

(2021). Online misinformation and vaccine hesitancy. Translational Behavioral Medicine, 11(12), 2194–2199. 10.1093/tbm/ibab128

26.

Gazali

(2014). Learning by clicking: An experiment with social media democracy in Indonesia. International Communication Gazette, 76(4–5), 425–439. 10.1177/1748048514524119

27.

Håkansson

, & Witmer

(2015). Social media and trust—A systematic literature review. Journal of Business and Economics, 6(3), 517–524. 10.15341/jbe(2155-7950)/03.06.2015/010

28.

Han

, Wang

, Zhang

, & Wang

(2020). Using social media to mine and analyze public opinion related to COVID-19 in China. International Journal of Environmental Research and Public Health, 17(8), 2788. 10.3390/ijerph17082788

29.

Hardt

(2008). Lasswell, Harold D. The International Encyclopedia of Communication. 10.1002/9781405186407.wbiecl009

30.

Hausman

, & Johnston

W. J.

(2010). The impact of coercive and non-coercive forms of influence on trust, commitment, and compliance in supply chains. Industrial Marketing Management, 39(3), 519–526. 10.1016/j.indmarman.2009.05.007

31.

Hobbs

(2011). The state of media literacy: A response to Potter. Journal of Broadcasting & Electronic Media, 55(3), 419–430. 10.1080/08838151.2011.597594

32.

Hou

, Gao

, & Heeks

(2011). The influence of institutional forces on employee compliance with information security policies. Proceedings of the 8th International Workshop on Security in Information Systems. 10.5220/000358790132014

33.

Hussain

, Shabir

, & Taimoor-Ul-Hassan. (2020). Cognitive needs and use of social media: A comparative study of gratifications sought and gratification obtained. Information Discovery and Delivery, 48(2), 12. 10.1108/IDD-11-2019-0081

34.

Hussain

(2020). Role of social media in COVID-19 pandemic. International Journal Frontier Sciences, 4(2), 2. 10.37978/tijfs.v4i2.144

35.

Ikoja-Odongo

, & Mostert

(2006). Information seeking behaviour: A conceptual framework. South African Journal of Libraries and Information Science, 72(3), 14. 10.7553/72-3-1112

36.

Intyaswati

, Maryani

, Sugiana

, & Venus

(2021). Social media as an information source of political learning in online education. Sage Open, 11(2). 10.1177/21582440211023181

37.

Javier

P. F.

, Ramon

D. G.

, Ana

G., Alves, M

M. C.

, & Julia

A. B. M.

(2021). Attitude towards vaccination among health science students before the COVID-19 pandemic. Vaccines (Basel), 9(6). 10.3390/vaccines9060644

38.

Kamboj

(2020). Applying uses and gratifications theory to understand customer participation in social media brand communities Perspective of media technology. Social Media Brand Communities, 32(1), 27. 10.1108/APJML-11-2017-0289

39.

Kastlunger

, Lozza

, Kirchler

, & Schabmann

(2013). Powerful authorities and trusting citizens: The Slippery Slope Framework and tax compliance in Italy. Journal of Economic Psychology, 34, 36–45. 10.1016/j.joep.2012.11.007

40.

Kemp

(2021). Digital 2021: Indonesia. Datareportal. https://datareportal.com/reports/digital-2021-indonesia

41.

Kock

(2020). WarpPLS© user manual: Version 7.0. ScriptWarp Systems. https://www.warppls.com/

42.

Kricorian

, Civen

, & Equils

(2022). COVID-19 vaccine hesitancy: misinformation and perceptions of vaccine safety. Human Vaccines & Immunotherapeutics, 18(1), 1950504. 10.1080/21645515.2021.1950504

43.

Leite

, Lindsay

, & Kumar

(2020). COVID-19 outbreak: Implications on healthcare operations. The TQM Journal, 10. 10.1108/TQM-05-2020-0111

44.

Lev-On

(2011). Communication, community, crisis: Mapping uses and gratifications in the contemporary media environment. New Media & Society, 14(1), 98–116. 10.1177/1461444811410401

45.

Lim

, & Nakazato

(2020). The emergence of risk communication networks and the development of citizen health-related behaviors during the COVID-19 pandemic: Social selection and contagion processes. International Journal of Environmental Research and Public Health, 17(11). 10.3390/ijerph17114148

46.

Liu

P. L.

(2020). COVID-19 Information seeking on digital media and preventive behaviors: The mediation role of worry. Cyberpsychology, Behavior, and Social Networking, 23(10), 677–682. 10.1089/cyber.2020.0250

47.

Mani

(2017). Culture-based communication approach in the relocation policy of street vendors in urban areas [Research Universitas Gadjah Mada]. Yogyakarta, Indonesia.

48.

Mani

, & Guntoro

(2020). Culture and design in public policy communication (in Indonesia) (Vol. 1). PT. Remaja Rosdakarya.

49.

Meier

K. J.

, & Morgan

D. R.

(1982). Citizen compliance with public policy: The national maximum speed law. Western Political Quarterly, 35(2), 16. 10.1177/106591298203500211

50.

Mohdali

, Isa

, & Yusoff

S. H.

(2014). The impact of threat of punishment on tax compliance and non-compliance attitudes in Malaysia. Procedia - Social and Behavioral Sciences, 164, 291–297. 10.1016/j.sbspro.2014.11.079

51.

Myers

D. G.

, & Twenge

J. M.

(2016). Social psychology (12th ed.). McGraw-Hill Education.

52.

Nasir

(2013). Role of media in a developed society. Interdisciplinary Journal of Contemporary Research in Business, 5(2), 407–415.

53.

Ndumbe-Eyoh

, & Mazzucco

(2016). Social media, knowledge translation, and action on the social determinants of health and health equity: A survey of public health practices. Journal of Public Health Policy, 37(Suppl. 2), 249–259. 10.1057/s41271-016-0042-z

54.

Ozili

(2020). COVID-19 in Africa: Socio-economic impact, policy response and opportunities. International Journal of Sociology and Social Policy t. 10.1108/ijssp-05-2020-0171

55.

Paek

H.-J.

, & Hove

(2021). Information communication technologies (ICTs), crisis communication principles and the COVID-19 response in South Korea. Journal of Creative Communications, 16(2), 213–221. 10.1177/0973258620981170

56.

Pentina

, & Tarafdar

(2014). From ‘information’ to ‘knowing’: Exploring the role of social media in contemporary news consumption. Computers in Human Behavior, 35, 211–223. 10.1016/j.chb.2014.02.045

57.

Perloff

R. M.

(2003). The dynamics of persuasion: Communication and attitudes in the 21st century (2nd ed.). Lawrence Erlbaum Associates.

58.

Powers

(2007). Persuasion and coercion: A critical review of philosophical and empirical approaches. HEC Forum, 19(2), 125–143. 10.1007/s10730-007-9035-4

59.

Rayani

, Rayani

, & Najafi-Sharjabad

(2021). COVID-19-related knowledge, risk perception, information seeking, and adherence to preventive behaviors among undergraduate students, southern Iran. Environmental Science and Pollution Research International, 28(42), 59953–59962. 10.1007/s11356-021-14934-y

60.

Roozenbeek

, Schneider

C. R.

, Dryhurst

, Kerr

, Freeman

A. L. J.

, Recchia

, van der Bles

A. M.

, & van

der Linden, S.

(2020). Susceptibility to misinformation about COVID-19 around the world. Royal Society Open Science, 7(10), 201199. 10.1098/rsos.201199

61.

Roşca

V. I.

(2020). Implications of Lewin’s field theory on social change. Proceedings of the International Conference on Business Excellence, 14(1), 617–625. 10.2478/picbe-2020-0058

62.

Sager

(2009). Governance and coercion. Political Studies, 57(3), 537–558. 10.1111/j.1467-9248.2008.00743.x

63.

Sahni

, & Sharma

(2020). Role of social media during the COVID-19 pandemic: Beneficial, destructive, or reconstructive? International Journal of Academic Medicine, 6(2), 6. 10.4103/IJAM.IJAM_50_20

64.

Saunders

B. J.

, & Goddard

(2002). The role of mass media in facilitating community education and child abuse prevention strategies. National Child Protection Clearinghouse Resource Sheets (16), 25. Australian Institute of Family Studies.

65.

Schramm

, & Roberts

D. F.

(1971). The process and effects of mass communication. University of Illinois Press.

66.

Sherchan

, Nepal

, & Paris

(2013). A survey of trust in social networks. ACM Computing Surveys, 45(4), 1–33. 10.1145/2501654.2501661

67.

Sholihin

, & Ratmono

(2021). SEM-PLS analysis with WarpPls 7.0 (In Indonesian). CV Andi Offset.

68.

Singhal

, & Kim

D. K. D.

(2021). The role of the communication discipline to tackle COVID-19: Interrogating positive deviations and critical discourses. Journal of Creative Communications, 16(2), 135–138. 10.1177/09732586211002930

69.

Sjostrom

(2006). Invocation of coercion context in compliance communication—power dynamics in psychiatric care. International Journal of Law and Psychiatry, 29(1), 36–47. 10.1016/j.ijlp.2005.06.001

70.

Torres

, Kelley

, Piña

, Garcia-Baza

, & Griffith

(2021). An Analysis of digital media data to understand parents’ concerns during the COVID-19 pandemic to enhance effective science communication. Journal of Creative Communications, 16(2), 168–189. 10.1177/09732586211000281

71.

Uznienė

(2012). Media—Agents of socialization. Regional Formation and Development Studies, 3(8), 9. 10.15181/RFDS.V8I3.583

72.

Vivian

(2008). The media of mass communication in Indonesia (8th ed.). Prenada Media Group.

73.

West

, & Turner

L. H.

(2018). Introducing communication theory: analysis and application (6th ed.). McGraw-Hill Education. PDFDrive.com

74.

WHO. (2021). Coronavirus disease (COVID-19) pandemic. https://www.who.int/emergencies/diseases/novel-coronavirus-2019

75.

Yanti

, Wahyudi

, Wahiduddin

, Novika

R. G. H.

, Arina

Y. M. D. a.

, Martani

N. S.

, & Nawan

(2020). Community knowledge, attitudes, and behavior towards social distancing policy as prevention transmission of COVID-19 in Indonesia. Journal Administrasi Kesehatan Indonesia, 8(2). 10.20473/jaki.v8i2.2020.4-14