COVID-19 preventive behaviors and digital health communication media usage model

Abstract More than two years have passed, and the coronavirus disease 2019 (COVID-19) is yet to be completely resolved. Campaigns on COVID-19 preventive behaviors have become crucial in tackling this issue among the public. Persuading the public to practice COVID-19 preventive behaviors remains to be a challenge. The current research aims to develop and test a model that can explain COVID-19 preventive behaviors by considering two factors: digital communication and psychological factors. This study employed a quantitative approach, wherein data were collected through an online survey. The sample consisted of 358 participants. Samples were selected using the purposive sampling method. SEM-PLS was used as an analytical tool in this study. The results of this research indicate that COVID-19 preventive behaviors are directly and positively influenced by behavioral intentions, digital media platforms, and communication exposure. Furthermore, COVID-19 preventive behaviors are indirectly influenced by perceived threat, subjective norms, perceived behavior control, awareness, knowledge, attitude, and message characteristics. Meanwhile, source credibility was proven to have neither direct nor indirect influence on COVID-19 preventive behaviors.


Introduction
In 2019, a new global health issue emerged, namely the coronavirus disease 2019 .The disease is caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) (Zewdie et al., 2022).The virus has become a global issue owing to its extremely high severity and rapid and expansive transmission (Aschwanden et al., 2021).Accordingly, the World Health Organization (WHO) declared it as a global pandemic on March 11, 2020(WHO, 2020).
For more than two years, the global community has been living under the shadow of the SARS-CoV-2 virus, and as of the end of 2022, COVID-19 is still not entirely over.Numerous countries and WHO have made various efforts to overcome COVID-19.One of the efforts that has been acknowledged as effective in preventing and controlling SARS-CoV-2 is to establish COVID-19 preventive behaviors in the population (Aschwanden et al., 2021).The WHO recommends several COVID-19 preventive behaviors, such as wearing face masks, social distancing, handwashing with soap and water, using hand sanitizer, self-isolation, avoiding spending time in crowded places, and taking a vaccine (Zewdie et al., 2022).Although COVID-19 preventive behaviors are needed by the public, getting them to practice COVID-19 preventive behaviors remains a challenge.In other words, it is important to improve COVID-19 preventive behaviors.
In order to improve COVID-19 preventive behaviors, health education associated with COVID-19 preventive behaviors is necessary to improve these behaviors (Bonell et al., 2020).During the COVID-19 pandemic, health education related to COVID-19 preventive behaviors can be achieved through digital communication media, such as social media, websites, and health applications (Mheidly & Fares, 2020).Governments in many countries are using digital media to educate the public about COVID-19 preventive behaviors.For example, to deal with the COVID-19 problem, the Indian government conducts health education using digital communication media, such as Facebook and Twitter (Roy et al., 2022).This digital communication media is the main key for the Indian government in health education during the COVID-19 pandemic (Roy et al., 2022).In Indonesia, the Indonesian government also relies on digital communication media to educate the public on handling COVID-19, such as website (@covid19.go.id),Facebook (@lawancovid19indonesia), Instagram (@lawancovid19_id), Twitter (@lawancovid19_id), and Applications Play store (@United Against COVID-19).
Digital communication media is a revolutionary communication media capable of eliminating inequities of access to health promotion and communication (Roy et al., 2022).The advantages of digital communication media for educating COVID-19 preventive behaviors are as follows: (1) the media has a very large audience and extensive coverage; (2) it is popular among the public; (3) it can be used to engage in two-way communication among users; (4) it can be used at any time to the user's liking; and (5) it can be used for virtual communication without having to meet face-toface (Dutta & Bhattacharya, 2023;Mat Dawi et al., 2021;Wadham et al., 2019).Furthermore, several studies have recognized the significance of digital communication media during the COVID-19 pandemic in various contexts (e.g., Afifi et al., 2022;Biswas et al., 2022;Mahmood et al., 2021;Rather, 2021;Riady et al., 2022;Zanuddin et al., 2021).
Several studies have been conducted on COVID-19 preventive behaviors.Most research on COVID-19 preventive behaviors has been conducted using psychological approaches, such as the Theory of Planned Behavior (TPB) (Li et al., 2021, Aschwanden et al., 2022;Park & Oh, 2022), Health Belief Model (HBM) (Hong et al., 2021;Shahnazi et al., 2020;Zewdie et al., 2022), and Protection Motivation Theory (PMT) (Barati et al., 2020;Ezati Rad et al., 2021;Prasetyo et al., 2020).Although the findings of some studies confirmed the theory used, several studies found a research result that was inconsistent with the theory (for example: Alagili & Bamashmous, 2021;Bronfman et al., 2021;Karimy et al., 2021;Mahindarathne, 2021;Mirzaei et al., 2021;Park & Oh, 2022).The inconsistent results of previous studies indicate that the COVID-19 preventive behavior model needs to be re-examined in a different context, including Indonesia.Furthermore, during the COVID-19 pandemic, the use of digital communication media experienced quite a significantly increased (Afifi et al., 2022;Kemp, 2020;Nguyen et al., 2020).Digital media platforms have become the most widely used media by the public to obtain various types of information, including COVID-19 and health information (Patmanthara et al., 2019;Suwana et al., 2020).In Indonesia, the government has also used digital communication media to disseminate COVID-19 related health information.However, there is a lack of previous studies on COVID-19 preventive behavior models that involve psychological factors derived from TPB, PMT, and HBM and digital health communication media-related factors.In other words, it is important to conduct research on COVID-19 preventive behaviors that involve not only psychological factors, but also digital health communication media-related factors.
According to the previous explanation, to fill the gaps in the literature, the objective of this research is to study COVID-19 preventive behaviors by involving not only psychological factors derived from TPB, PMT, and HBM, but also digital health communication media-related factors.More specifically, this study aims to develop and test a COVID-19 preventive behavior model by involving awareness, knowledge, attitude, behavioral intention, perceived behavioral control (PBC), subjective norm, perceived threat, health communication exposure, source credibility, message characteristics, and digital health communication media platforms.The integration of psychological factors and communication media-related factors can be carried out considering that various previous studies have also integrated these factors in different contexts (e.g., Nguyen & Le, 2021;Riady et al., 2022;Rivas et al., 2021;Xin et al., 2021).This research objective needs to be achieved because this research was needed theoretically and practically.Theoretically, this research filled a research gap that has not been done by previous studies.This research was able to empirically explain the COVID-19 prevention behaviors by involving psychological factors and digital health communication media-related factors.Practically, the government and other health education related parties can use this research model as a guide in carrying out a health education program about COVID-19 prevention behaviors.In other words, the research results can assist the government and other health education related parties in mitigating the risk of COVID-19 pandemic through an appropriate health education strategy.

Covid 19 preventive behavior
Preventive behavior is defined as "any behavior that people engage in spontaneously or can be induced to perform with the intention of alleviating the impact of potential risks and hazards in their environment" (Kirscht, 1983).In the context of health, preventive behavior can be defined as "any behavior that according to professional medical and scientific standards, prevents disease or disability and/or detects disease in asymptomatic stage, and which is voluntarily undertaken by a person who believes himself to be healthy" (Langlie, 1979).Based on the definitions above, this study defined COVID-19 preventive behaviors as measures that can be undertaken by individuals to prevent the risks of COVID-19, in which the effectiveness of the measures has been recognized by health experts.
The existing literature explains that there are various measures that people can undertake to prevent the spread of COVID-19.Nguyen et al. (2020) explains that COVID-19 preventive behaviors can focus on two aspects: personal and community.Personal preventive behaviors refer to measures that can be taken to avoid personally contracting the COVID-19 virus, such as physical distancing, wearing a face mask, cough etiquette, regular handwashing, use of alcohol-based hand sanitizers, body temperature checks, and disinfecting mobile phones, et cetera (Nguyen et al., 2020).Meanwhile, community preventive behaviors refer to communal measures that can be undertaken by individuals to avoid being infected by the COVID-19 virus within the community, such as avoiding meetings, large gatherings, going to the market, avoiding travel in a vehicle/bus with more than 10 persons, and not traveling outside the local area during lockdown (Nguyen et al., 2020).
COVID-19 preventive behaviors can be explained using various theoretical approaches such as TPB (Aschwanden et al., 2021;Li et al., 2021;Park & Oh, 2022), HBM (Hong et al., 2021;Shahnazi et al., 2020;Zewdie et al., 2022); and Hierarchy of Effect Theory/HET (Masek et al., 2022;Kolte et al., 2022).The combination of factors found in these models can provide a more comprehensive elaboration on the phenomenon of COVID-19 preventive behaviors.Moreover, considering that health communication during the COVID-19 pandemic has tended to utilize digital communication media, digital communication media-related factors can provide more comprehensive explanations of COVID-19 preventive behaviors.Given this, we proposed a COVID-19 preventive behavior model that involves awareness, knowledge, attitude, behavioral intention, perceived behavioral control (PBC), subjective norm, perceived threat, health communication exposure, source credibility, message characteristics, and digital health communication media platforms.Figure 1 illustrates this conceptual model.

Behavioral intention (BI)
BI is a construct identified by the TPB.In TPB, behavioral intention can be described as a concept that represents a motivational factor that influences actual behavior (Ajzen, 1991).This indicates a person's readiness to engage in a particular behavior (Ajzen, 1991).More specifically, BI can be measured by willingness to perform the behavior and plan to perform the behavior (Ajzen, 1991).Thus, in this study, BI represents a person's motivation to engage in COVID-19 preventive behaviors.
This construct is used by the TPB to explain behavioral formation (Ajzen, 1991).Specifically, according to the TPB, BI positively influences behavior.In the context of COVID-19 preventive behaviors, several studies have found the positive impact of BI on COVID-19 preventive behaviors (Chen & Chen, 2020;Hong et al., 2021;Park & Oh, 2022;Sangeeta & Tandon, 2021).Thus, the first hypothesis of this study was formulated as follows: H1: BI influences COVID-19 preventive behaviors positively and significantly.

Attitude
A definition of attitude has been proposed by various researchers (Altmann, 2008).Ajzen (1991) proposed the most popular definition of attitude.Attitude was defined as "the degree to which a person has a favorable or unfavorable evaluation or appraisal of the behavior in question" (Ajzen, 1991).This definition has also been adopted in COVID-19 related studies, such as Twum et al. (2021), Fenitra et al. (2021), and Jain et al. (2022).

Knowledge
Knowledge is a complex construct discussed by numerous scholars (Jiang & Rosenbloom, 2014).This construct reflects cognitive aspects (Duffett, 2020).Hosseinzadeh et al. (2020) explained that knowledge is "the concept, skill, experience, and vision that provide a framework for creating, evaluating, and using information".In the existing literature, the concept of health knowledge is specifically applied according to the examined context, such as knowledge of diseases (Jirattikorn et al., 2020;Khajebishak et al., 2021;Rajkumar & Romate, 2020), knowledge of oral nutrition (Aydin et al., 2022;Limbu et al., 2019;Tam et al., 2019), and oral health knowledge (Abu-Gharbieh et al., 2019;Al-Wesabi et al., 2019;Riad et al., 2022).Therefore, in this study, knowledge was examined in the context of knowledge related to COVID-19 preventive behaviors.
According to the HET, knowledge positively influences attitudes (Masek et al., 2022).Several empirical studies have confirmed the positive relationship between knowledge and attitudes in various contexts (Suki, 2016;Wang et al., 2020;Xin & Seo, 2020), including health behaviors (Ghazali et al., 2017).Therefore, this research expected that knowledge would positively influence attitudes toward COVID-19 preventive behaviors.The third hypothesis is as follows.

Awareness
Awareness can be defined as "the capacity to become the object of one's own attention" (Morin, 2006).Awareness refers to an individual's ability to understand and adapt to new situations (Anzanpour et al., 2017;Lewis et al., 2011).More briefly, awareness is "an affirmative response" to something, be it an object or a situation (Whaley-Connell et al., 2009).
Awareness is closely related to knowledge.Based on HET, awareness positively affects attitudes.Previous studies have shown that awareness positively influences knowledge (for example: Koohang et al., 2022;Mohiuddin et al., 2018;Zhao et al., 2020).Thus, this research expected that awareness would positively influence knowledge of COVID-19 preventive behaviors.The fourth hypothesis is as follows.

Perceived behavior control (PBC)
The PBC is a construct identified by the TPB.PBC refers to an individual's belief in his/her control over a behavior (Wallston, 2005).According to Ajzen (1991), PBC can be defined as "perceived ease or difficulty of performing the behavior."Furthermore, it represents the availability of resources and opportunities for an individual to perform an action (Ajzen, 1991).In other words, PBC describes the limits, obstacles, and struggles that occur when a person performs a behavior (Ajzen, 1991).Therefore, this study defined PBC as an individual's perceived ease or difficulty in applying COVID-19 preventive behaviors by considering the resources one has and the opportunity to perform these behaviors.
The TPB argued that PBC has a positive impact on BI and actual behavior (Ajzen, 1991).Several empirical studies have shown that PBC is a predictor of BI (Sumaedi et al., 2021a).During COVID-19 pandemic, several scholars have found that PBC positively affects health behavior (e.g., Ahmad et al., 2020;Liu et al., 2021;Park & Oh, 2022;Twum et al., 2021).Thus, we expected that PBC would positively influence COVID-19 preventive behaviors and the BI for COVID-19 preventive behaviors.The fifth and sixth hypotheses of this study are formulated as follows: H5: Perceived behavioral control influences BI of COVID-19 preventive behaviors positively and significantly.

Subjective norm
Subjective norm is "the perceived social pressure to perform or not perform the behavior" (Ajzen, 1991).This definition has frequently been adopted by many scholars (Barbera & Ajzen, 2020;Twum et al., 2021;Sumaedi et al., 2020Sumaedi et al., , 2021aSumaedi et al., , 2021b)).This definition was adopted in the present study.More clearly, subjective norm refers to an individual's perception of social pressures from people they consider important to perform COVID-19 preventive behaviors.
TPB argues that a person's BI can be positively influenced by subjective norms (Ajzen, 1991).Previous studies, such as Astrini et al. (2021), Yarmen et al. (2016), andLiu et al. (2021), have shown the positive influence of subjective norms on BI.In the context of the COVID-19 study, the positive impact of subjective norms on the BI of health behaviors was also confirmed (e.g., Chen & Chen, 2020, Sumaedi et al., 2020, 2021a, 2021b;Park & Oh, 2022;Twum et al., 2021).The seventh hypothesis proposed in this study is as follows: H7: Subjective norm influences BI of COVID-19 preventive behaviors positively and significantly.

Perceived threat of COVID-19
Perceived threat can be defined as "the anticipation of harm that is based on the cognitive appraisal of an event or cue that is capable of eliciting the individual's stress response" (Carpenter, 2005).Three keywords can be used to describe perceived threats: anticipation of harm, cognitive appraisal, and stress response (Carpenter, 2005).In the health context, perceived threat is a construct that discusses two aspects: severity and susceptibility (Hong et al., 2021;Mirzaei et al., 2021).

Health communication exposure
Health communication exposure is a factor that needs to be considered in health education (Han & Xu, 2020).In communication literature, exposure is a part of the communication process that represents how often receivers receive and engage with an information message so that they respond to it (Lefevre et al., 2019).According to Nunez-Smith et al. ( 2010), communication exposure covers two aspects: content (exposure from the aspect of information substance) and quantity (exposure from the aspect of the number of media).Thus, this study defined health communication exposure as how often someone receives and engages with COVID-19 preventive behavior information from a digital health communication media platform.
The existing health literature showed that health communication exposure has positive impact on health behavior (e.g., Faasse & Newby, 2020;Fenitra et al., 2021;Xin et al., 2021) It also empirically influences attitude toward health behavior (Rivas et al., 2021), knowledge of health behavior and awareness toward health behavior (Bago & Lompo, 2019)

Source credibility
According to Rains and Karmikel (2009), source credibility can be defined as ''judgements made by a perceiver concerning the believability of a communicator" (O'Keefe, 2016)"."Source credibility may include judgements of the attractiveness, expertise, and trustworthiness of the message source (Wiedmann & von Mettenheim, 2020).Given this, this study defined source credibility as someone's judgements of attractiveness, expertise, and trustworthiness of the message source in informing them about COVID-19 preventive behaviors.

Variables and measures
This study involved 12 research variables, namely digital health communication media platforms (DHCMPs), message characteristics, source credibility, health communication exposure, perceived threat of COVID-19, subjective norm, perceived behavior control, awareness, knowledge, attitude, behavioral intention, and COVID-19 preventive behavior.To ensure content validity, the indicators for each variable were adopted from previous human behaviour studies that discussed the relevant variable (Tari et al., 2007).For example, subjective norm was measured by three indicators that adapted from Astrini et al. (2021), Bronfman et al. (2021), andSumaedi et al. (2020;2021b).More completely, Table 1 lists the variables and indicators with the reference source.Since the indicators were adopted from diverse human behaviour literature, to ensure that the indicators are understood by respondents according to the operational definition of each variable, during the instrument development we performed wording test by asking 10 respondents whether they understood each question.They confirmed that every question in the questionnaire was understood.Indicators were assessed using a five-point Likert scale ranging from 1 (extremely disagree) to 5 (extremely agree).

Data collection and respondents
Owing to physical movement limitations during the COVID-19 pandemic, an online survey was used to collect data.There were 419 respondents wanted to participate voluntarily and gave informed consent for this survey.However, there were 61 respondents that can't be analyzed further because they didn't meet the sample criteria of this study and/or didn't completely fill out the questionnaire.Thus, the samples of this research are 358 respondents.The number of these samples have met the sample size needed.According to Hair et al. (2010), the minimum sample size that must be taken in SEM is at least 5 times the number of indicators.In this study, the total of indicators used to measure 12 variables were 56 items.In other words, the minimum sample size for this study was 280 respondents.Moreover, calculating the minimum sample size can be performed by using G*Power analysis (Faul et al., 2009).This analysis is the best estimates the statistical power for sample size analysis (Soomro et al., 2023).Based on the calculation of G*Power software program (version 3), in order to achieve small effect size (Kang, 2021), the minimum number of samples that must be taken in this research was 178.
The sample criteria were as follows: (1) aged 17 years and above; (2) living in the Greater Jakarta area (Jakarta, Bogor, Depok, Tangerang, Bekasi-Jabodetabek) and Yogyakarta Special Region, Indonesia; and (3) obtained/searched for information about COVID-19 preventive behaviors from digital media platforms (e.g., YouTube, Facebook, Instagram, TikTok, etc.) during the COVID-19 pandemic.The survey involved only the residents of the Greater Jakarta area (Jakarta, Bogor, Depok, Tangerang, Bekasi-Jabodetabek) and Yogyakarta Special Region, since these regions can be categorized as the regions with the highest rate of Internet use in Indonesia (BPS-Statistics Inodonesia, 2019).The respondents' profiles are listed in Table 2.This research received ethical clearance from the Research Ethics Committee in Faculty of Psychology & Socio-Cultural Sciences at Universitas Islam Indonesia (No: 1365/Dek/70/DURT/VII/2022).
In order to prevent potential survey bias, we have performed several procedural controls proposed by previous researchers.Based on Kock et al. (2021), the source of survey bias consists of respondent related source and measurement related source.In order to mitigate the respondent related source, we didn't ask the questions that potentially cause the social desirability bias in Indonesia, such as income, tribes, religion, race, and political preference (Conway & Lance, 2010).In order to mitigate the measurement related source, several actions were performed, such as performing wording test, providing clear questionnaire instructions, keeping simple and non-ambiguous survey items, concise survey length, and anonymous responses (Kock et al., 2021;Podsakoff et al., 2012) and ensuring that there is no overlap indicator for each variable (Conway & Lance, 2010).
• People whose opinions matter to me think that I should practice COVID-19 preventive behaviors (SNM3).

Measurement model
Construct reliability was tested using Cronbach's alpha and composite reliability (CR) values, while convergent validity was tested using item loading and average variance extracted (AVE) values (Bagozzi & Yi, 2012;Fornell & Larcker, 1981;Hair et al., 2010).As shown in Table 3, all variables have a significant item loading value, the item loading value (range 0.633-0.96)exceeds the minimum threshold of 0.6 (Hair et al., 2010), and the Cronbach's alpha value (0.71-0.94) also exceeds the minimum threshold of 0.7 (Hair et al., 2010).The CR values for all variables exceeded

Monthly income
• None/No income 47,1 • ≤ IDR 3,000,000 18.6 • IDR 3,000,001-6,000,000 8.7 • IDR 6,000,001-10,000,000 the minimum threshold of 0.7, and nearly all variables had an AVE greater than 0.5 (Fornell & Larcker, 1981;Hair et al., 2010).The AVE value of a variable, DHCMPs, was slightly below 0.5 (AVE DHCMPs = 0.464).Previous studies claim that this condition is acceptable if other supporting indicators satisfy the standard (Lam, 2012).Based on these results, the measurement model is reliable and has convergent validity.

Theoretical implications
Based on Lewis and Feiring (1992) and Ashari et al. (2022), the direct effect shows that a variable has an influence on COVID-19 preventive behaviors without going through a mediating variable.In other words, changing these variables will directly cause changes in COVID-19 preventive   behaviors.Meanwhile, the indirect effect shows that the effect of a variable on COVID-19 preventive behaviors is through a mediating variable.Thus, changing these variables will not directly cause changes in COVID-19 preventive behaviors but it will cause changes in the mediating variables first.
This study found that PBC had no direct impact on COVID-19 preventive behaviors, but PBC indirectly affected COVID-19 preventive behaviors through behavioral intention.This finding was supported by Park and Oh (2022) and Trifiletti et al. (2022).However, this finding differs from that of the TPB.According to the TPB, PBC has a direct and indirect effect on behavior.The absence of PBC's direct influence on COVID-19 preventive behaviors may be due to the context of this research.Considering that COVID-19 is a new virus for the public, making it difficult for them to directly change their behaviors to COVID-19 preventive behaviors without strong motivation, even though they have enough capacity to perform these behaviors.This condition made PBC indirectly affect COVID-19 preventive behaviors through behavioral intentions.
This study showed that subjective norms have a positive and significant impact on behavioral intention toward COVID-19 preventive behaviors.This finding is in accordance with TPB.This finding is also supported by previous studies (e.g., Ahmad et al., 2020, Sumaedi et al., 2020, 2021a, 2021b;Liu et al., 2021;Twum et al., 2021).This study found that perceived threat positively and significantly influences awareness, knowledge, and attitude toward COVID-19 preventive behaviors.This finding supports those of previous studies (e.g.(Rather, 2021Wnuk et al., 2020, Paige et al., 2018)., Perceived threat did not significantly influence behavioral intention and COVID-19 preventive behaviors.Although several previous studies also found a non-significant effect of perceived threat of COVID-19 on behavioral intention (e.g., Sumaedi et al., 2020;Walrave et al., 2020;Yang et al., 2022)  With regard to digital communication media factors, this study revealed several findings.First, digital health communication platforms have a significant and positive influence on awareness of and COVID-19 preventive behaviors.This finding is in accordance with previous findings by Mahmood et al. (2021), Li andLiu (2020), andAl-Dmour et al. (2020).Second, health communication exposure had a positive and significant impact on awareness, attitude, and COVID-19 preventive behaviors.This finding is in line with those of previous studies, such as Faasse and Newby (2020), Bago andLompo (2019), andRivas et al. (2021).Third, health communication message characteristics only had significant and positive effects on knowledge and attitudes toward COVID-19 preventive behaviors.This finding supports those of several other researchers (e.g., Borah et al., 2021;Carfora & Catellani, 2021;Ezeah et al., 2020;Rains & Karmikel, 2009).
Another finding related to digital communication media factors is the non-significant effect of health communication source credibility on awareness, knowledge, attitude, behavioral intention, and COVID-19 preventive behaviors.This finding differs from those of previous studies (Gehrau et al., 2021;Hoda, 2016;Vlasceanu & Coman, 2022).The difference may be due to the context of the research being different from other studies.COVID-19 is a novel disease, which implies that knowledge related to its handling of COVID-19 remains limited during the initial appearance of the virus.Furthermore, the condition also has an impact on the public, who often find different perspectives given by experts in handling the virus.This condition may reduce the importance of source credibility perceived by the public.Furthermore, several popular digital media platforms were still able to provide information in text format (e.g., WhatsApp, Facebook, websites).Text format information might have made it difficult for digital media users to confirm whether the source of information is credible, even though the information already included the name of the author(s) with their medical expertise or degree.This might have occurred because anyone can create information that is actually hoaxes by mentioning that the source of information is a medical expert.This might have been the reason why many people do not consider the source credibility of digital communication media in practicing COVID-19 preventive behaviors.Theoretically, based on The Elaboration Likelihood Model (Petty & Cacioppo, 1981), this finding indicated that the research subjects tended to select the central route rather than the peripheral route in information processing.In other words, in the context of COVID-19 preventive behaviours, the research subjects tended to consider the information content than information source.In the other context than COVID-19 preventive behaviours, this finding is in line with Park et al. (2007) and Wu and Wang (2011).
Based on the previous discussions, it can be stated that this research has offered at least two insights in addressing the complex problem, namely health behaviour during a pandemic, in the context of developing country.First, we can integrate psychological factors and communication media-related factors in order to explain health behaviour during a pandemic.We implemented this approach in the context of digital health communication media.Future research may apply this approach to other health communication media.Second, this research has identified that people tended to select the central route rather than the peripheral route in information processing in this context.In other words, message characteristic tended to be more important than source credibility in the context of health communication during a pandemic in developing country.

Managerial implications
Based on these theoretical implications, this study has several managerial implications.In general, the managerial implications proposed in this study are oriented toward psychological aspects and digital health communication media.First, regarding health education on COVID-19 preventive behaviors, the government needs to consider the public's cognitive, affective, and conative/behavioral aspects.In terms of the cognitive aspect, health education on COVID-19 preventive behaviors should be able to increase public awareness and knowledge of COVID-19 preventive behaviors.In terms of the affective aspect, health education also needs to evoke feelings of positive emotions, fun, and a liking for COVID-19 preventive behaviors.As for the conative/ behavioral aspect, COVID-19 preventive health education needs to motivate the public to practice such behaviors.
Second, when providing health education on COVID-19 preventive behaviors, fear of COVID-19 needs to be instilled among the public.People need to feel that the disease is extremely dangerous, and the chance of contracting COVID-19 is high.In relation to this, the government can periodically provide information on the death rate of COVID-19 to the public.
Third, the government can also inform the public that practicing COVID-19 preventive behaviors is easy and requires minimal effort.Fourth, when campaigning for COVID-19 preventive behaviors, the government can involve influential figures in the community.These influential figures may include celebrities, influencers, religious figures, health experts, public officials, etc.The government can also include housewives as drivers of household health.The objective was to create a mutually supportive social environment for practicing COVID-19 preventive behaviors.References from important figures may motivate individuals to practice COVID-19 preventive behaviors.
Fifth, the government needs to utilize various DHCMPs when campaigning for COVID-19 preventive behaviors.This means that a health message about COVID-19 prevention should be disseminated through a single medium.The message must be extensively distributed through various DMPs, such as WhatsApp, TikTok, Twitter, Facebook, Instagram, YouTube, websites, and health applications.Such measures are aimed at getting more people to receive information about COVID-19 preventive behaviors.
Sixth, information disseminated through various platforms must also be delivered intensively.If possible, information about COVID-19 preventive behaviors should be disseminated daily over a long period.This is intended to repeatedly expose the public to such information so that they are consciously or unconsciously encouraged to practice COVID-19 preventive behaviors.
Lastly, when campaigning for COVID-19 preventive behaviors, the government needs to ascertain that the contents of messages disseminated to the public are of good quality.This is so that each message that the public receives is true (not hoaxes) and easily understood.Accordingly, before the contents of messages pertaining to COVID-19 preventive behaviors are distributed to the wider public, the messages should be pre-tested on members of the public to ensure that the contents meet several criteria, that is, easy to understand, accurate/true, as necessary, up-to-date, and detailed.

Conclusion, limitation and future research
COVID-19 preventive behaviors can be viewed as an effective method for suppressing the spread of COVID-19 in the population.This study developed and tested a model that can explain COVID-19 preventive behaviors.This study revealed that COVID-19 preventive behaviors are not influenced only by psychological factors.Other factors related to digital health communication media have also been confirmed to have an impact on COVID-19 preventive behaviors.These effects can be applied both directly and indirectly.Behavioral intention is a psychological factor that has a direct and positive influence on COVID-19 preventive behaviors is behavioral intention.Other psychological factors that have been confirmed to have positive and indirect effects on COVID-19 preventive behaviors are perceived threat, subjective norms, PBC, awareness, knowledge, and attitude.On the other hand, DHCMPs and communication exposure have been proven to have positive and direct impacts on COVID-19 preventive behaviors.Meanwhile, message characteristics have a positive and indirect effect on COVID-19 preventive behaviors.In the current study, source credibility was confirmed to have neither a direct nor indirect influence on COVID-19 preventive behaviors.
Although interesting findings were obtained in this study, some limitations remain.The main limitation of this research is that the data were obtained using the online survey method and purposive sampling technique.The online survey method was necessary because it facilitated enumerators/researchers to avoid direct physical contact with respondents.The purposive sampling technique caused the collected data to be disproportionate.In this study, the respondents were dominated by young students who were students and without income.Furthermore, it may be impossible to generalize these findings to other contexts.Accordingly, we suggest that future research use better sampling techniques.Future studies could test this research model in other regions.Several determinants of health behaviors can also be appended to enrich our findings.Examples of other determinants include personal characteristics, health consciousness, perceived healthiness, digital health literacy, attention to health information, and false information on digital communication media.
. Therefore, this study expected health communication exposure positively influences COVID-19 Preventive behaviors, behavioral intention of COVID-19 Preventive behaviors, attitude toward COVID-19 Preventive behaviors, knowledge of COVID-19 Preventive behaviors and awareness of COVID-19 Preventive behaviors.Therefore, the eighteenth, nineteenth, twentieth, twenty-first, and twenty-second hypotheses of this research are formulated as follows.H18: Health communication exposure influences awareness of COVID-19 preventive behaviors positively and significantly.H19: Health communication exposure influences knowledge of COVID-19 preventive behaviors positively and significantly.H20: Health communication exposure influences attitude toward COVID-19 preventive behaviors positively and significantly.H21: Health communication exposure positively and significantly influences behavioral intention toward COVID-19 prevention.H22: Health communication exposure influences COVID-19 preventive behaviors positively and significantly.

H28:
Message characteristics influences awareness of COVID-19 preventive behaviors positively and significantly.H29: Message characteristics influences knowledge of COVID-19 preventive behaviors positively and significantly.H30: Message characteristics influences attitude toward COVID-19 preventive behaviors positively and significantly.H31: Message characteristics influences behavioral intention of COVID-19 preventive behaviors positively and significantly.H32: Message characteristics influences COVID-19 preventive behaviors positively and significantly.

Figure
Figure 2. Empirical results of the structural path model.Value on path: p-value, R 2 : coefficient of determination.

Table 4 . Fornell-Larcker criterion analysis result
To improve COVID-19 preventive behaviors, it is important to develop a model that can be used to understand COVID-19 preventive behaviors.Several researchers have developed a COVID-19 preventive behavior model.However, there is a lack of research that integrates psychological and digital health communication-related factors to understand COVID-19 preventive behaviors.This research fills this gap in the literature.More specifically, this research has developed and tested a COVID-19 preventive behavior model by considering not only psychological factors (e.g., perceived threat, subjective norm, perceived behavior control, awareness, knowledge, attitude, and behavioral intention) but also factors relating to digital health communication (e.g., platforms, message characteristics, source credibility, and exposure).This research found that digital health communication media-related factors can directly influence COVID-19 preventive behaviors.The digital health communication media-related factors can also indirectly affect COVID-19 preventive behaviors through the mediating role of psychological factors.This research has showed that digital health communication media-related factors can be integrated with psychological factors for improving COVID-19 preventive behaviors.More specifically, the explanations of the findings of this research are as follows.

Table 7 . Hypothesis and path coefficients significance Testing results
Mirzaei et al. (2021)s (2021)iors, e.gAlagili and Bamashmous (2021);Karimy et al. (2021);Mahindarathne (2021);Mirzaei et al. (2021), this finding is not in line with HBM.This finding may also be due to the fact that COVID-19 is a new disease.This caused someone to lack awareness, knowledge, and attitudes toward the behaviors needed to face COVID-19.On the other hand, according to HET, behavior is formed through three stages: cognitive, affective, and conative.Someone who has a high perception of COVID-19 May not perform COVID-19 preventive behaviors since he/she was not aware, knew, and liked the behavior.This condition caused a non-significant direct effect of the perceived threat of COVID-19 on COVID-19 preventive behaviors and behavioral intention.