Introduction

The outbreak of the respiratory disease caused by the novel coronavirus disease (COVID-19) since December 2019 has seriously affected people’s health and lives all over the world (WHO, 2020b). Through great efforts by governments, public health sectors, doctors, and individuals, the development of COVID-19 has shown a generally stable and sporadic trend and the threat to the public has greatly reduced (Kowalski et al., 2020). Nevertheless, there is still a risk of transmission and infection, leading to continuously causing threats and inconveniences (WHO, 2022).

Confronting with this unexpected public health challenge, individuals are encouraged and even required to adopt proactively preventive actions (Breakwell et al., 2021; Duan et al., 2022; Farooq et al., 2020; Pan & Liu, 2022) to protect themselves and to control transmission of COVID-19. One of the important actions that individuals are likely to conduct actively or passively is to seek and use the information related to COVID-19 (Dreisiebner et al., 2022; Montesi, 2021). Specifically, they would access real-time information about COVID-19, look into the facts when encountering uncertainties, and capture informational assistance for health management (Chon & Park, 2021; Kim & Hong, 2021). These information behaviors would bring individuals a lot of benefits including accumulating knowledge about COVID-19, mitigating adverse health conditions, and reducing anxieties and worries (Blasco-Belled et al., 2020; Jungmann & Witthoft, 2020; Liu, 2020; Soroya et al., 2021). For example, Blasco-Belled et al. (2020) found that individuals who are more willing to use information processing strategies would find enough information during COVID-19 outbreaks and further increase their life satisfaction. Jungmann and Witthoft (2020) noted that timely accessing to and communicating accurate information about the pandemic through the media is effective for reducing an individual’s anxiety. Finset et al. (2020) indicated that effective health information communication actions can address uncertainties and fears and further promote necessary behavioral readjustments. It is therefore no surprise that the importance of implementation of online information actions is repeatedly emphasized by governments and public health sectors for individuals in the epidemic of COVID-19 (Kim & Hong, 2021; Montesi, 2021; Pan et al., 2020; Zimmerman, 2021).

Besides online information actions, the actual personal preventive actions are suggested for individuals to adopt as well. The major recommended and useful specific actions cover receiving vaccinations, performing hand hygiene frequently, wearing a facemask, and kee** a secure social distance in public areas (Kowalski et al., 2020; Lurie et al., 2020; Pan & Liu, 2022; Shelus et al., 2020). These preventive actions would directly protect individuals from COVID-19 and thus play a very critical role in COVID-19 prevention (Breakwell et al., 2021; WHO, 2022).

Being aware of the benefits and significance of individual online preventive actions, i.e., online information actions, and offline preventive actions against COVID-19, scholars have made great efforts on investigating these two kinds of actions. An important branch of studies is to identify and examine the factors that influence individual preventive actions. The factors indicated in the prior studies include individual protection motivation (Shelus et al., 2020), situational motivation (Chon & Park, 2021; Kim & Hong, 2021), personal value (Lake et al., 2021), social norms (Pan & Liu, 2022), and risk perception factors (Granderath et al., 2021). Of those factors, motivational factors act as the utmost role in stimulating individual online and offline actions against COVID-19 (Dodd et al., 2021; Kim & Hong, 2021; Lunn et al., 2020). Hence there is a need to study the motivations of individuals to implement online and offline preventive actions during the COVID-19 epidemic.

For individual online preventive actions, the situational motivation embodied in the situational theory of problem solving (STOPS) (Kim & Grunig, 2011) was found and verified to be one of most important motivations (Chon & Park, 2020; Kim & Hong, 2021; Lee et al., 2022). The motivations of individuals conduct offline preventive actions vary from action to action. Some key motivations mentioned in past studies that stimulate individuals’ preventive actions against COVID-19 are presented in Table 1.

Table 1 Individual motivations to conduct preventive actions against COVID-19
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The aforementioned studies provide us a solid knowledge to understand individual online and offline preventive actions during the COVID-19 epidemic and their influential factors especially motivational factors. However, there are three issues that worth looking into further while answering what motivate individuals to conduct online and offline preventive actions against COVID-19. Firstly, we look into individual online and offline preventive actions equally and simultaneously. A major reason is that both of them are important for individuals to deal with the challenges of COVID-19 (Breakwell et al., 2021; Kim & Hong, 2021; Lunn et al., 2020). Another reason is that these two actions are correlated rather than independent (Farooq et al., 2020; Kim & Hawkins, 2020; Liu, 2020). However, to our knowledge, few studies examine the relationship between these two kinds of preventive actions empirically. Secondly, this study investigates the influence of three motivations, i.e., situational motivation, concern-for-self, and concern-for-others, on individual online and offline preventive actions drawing on the STOPS theory (Kim & Grunig, 2011) and self-concern and other-orientation theory (De Dreu, 2006; De Dreu & Nauta, 2009). The aforementioned studies indicated that multiple motivations have influence on individual preventive actions and these three motivations were verified to play a critical role. Regarding online preventive actions, prior studies mainly concentrated on the situation motivation while neglecting other motivations such as concern-for-self and concern-for-others that are likely to exert influence as well. Finally, this study thinks that the three motivations are situation-specific and goal-oriented in nature instead of personal inherent characteristics. It means that these three motivations would be activated by individual perceptions of practical conditions related to COVID-19 (Baranik et al., 2022; Ospina et al., 2021; Tang et al., 2017). As a consequence, this study focuses on three situational factors highlighted in the STOPS theory, i.e., problem recognition, involvement recognition, and constraint recognition, and further investigate their influence on situational motivation, concern-for-self, and concern-for-others motivation.

Kee** in mind these three issues, this study identifies what has motivated individuals’ online and offline preventive actions against COVID-19 by incorporating self-concern and other-orientation theory into STOPS theory. Through an online survey among 628 individual citizens in Chinese cities that have infected COVID-19 cases during the time of survey, this study shows how an individual’s online preventive actions positively influence her/his offline preventive actions, and how individual perceptions of COVID-19 situation stimulate the three motivations, i.e., i.e., situational motivation, concern-for-self, and concern-for-others, and subsequently fuel individual online and offline preventive actions. The findings of this study enrich the extant literature on individual preventive actions by connecting online preventive actions with offline actions and showing the influence of motivations and their antecedents. Furthermore, our study on one hand advances STOPS theory by offering evidence that supports the utility of STOPS in the context of individual preventive actions against COVID-19. On the other hand, the findings extend STOPS by infusing concern-for-self and concern-for-others motivation.

The rest of this paper is organized as follows: Sect. 2 presents the theoretical framework and hypotheses. The followed section demonstrates the research methodology of this study, including descriptions of its empirical setting, sample characteristics, and measures. In Sect. 4, we test our hypotheses and present analysis results. Section 5 discusses the findings as well as implications of this study. Section 6 concludes the study.

Theory and hypotheses

Individual preventive actions against COVID-19

There is a dynamic relationship between human actions and infection transmission during epidemics (Poletti et al., 2009). Accordingly, the adoption of protective actions contributes to transmission scenarios and epidemic spread. The following individual actions play a protective and preventive role during the COVID-19 outbreak.

As immunization is one of the most successful and cost-effective health interventions to prevent infectious diseases, vaccines against COVID-19 are considered to be of great importance to prevent and control COVID-19 (Lurie et al., 2020; Yang et al., 2020). Additionally, general preventive actions are also important for individuals to cope with COVID-19 and its negative effects (WHO, 2022). According to the current evidence, the COVID-19 virus is primarily transmitted between people via respiratory droplets and contact routes (Abdelhafiz et al., 2021; Liu et al., 2020). As a result, the use of a medical mask can prevent the spread of infectious droplets from a symptomatic infected person (source control) to someone else and potential contamination of the environment by these droplets (Canini et al., 2010; Pan & Liu, 2022; Shelus et al., 2020). The WHO (2020a) announced that the public should wear masks not just to protect the wearer but also to protect others from being infected by the wearer. In addition to the measures mentioned above, the general preventive actions such as kee** social distance (Huang et al., 2021; Oosterhoff et al., 2020), taking care of personal hygiene (Daverey & Dutta, 2021), and following guidelines (Nelson-Coffey et al., 2021) can help individuals to defend COVID-19. This study mainly concentrates on these recommended useful general preventive actions that individuals are likely and able to conduct in the time of COVID-19 epidemic.

Besides the aforementioned actual actions, information is highlighted as a central role in supporting individuals to resolve the problems brought by COVID-19 (Liu, 2020; Pan et al., 2020). There is a tremendous volume of information related to COVID-19 that were posted and transmitted on the social media and traditional media during the COVID-19 epidemic (Granderath et al., 2021; Liu, 2020). With respect to this distributed information, an individual may conduct three kinds of actions frequently. The one is to acquire information that an individual may concern about or want to have to solve his/her problems. Another action is to scan and select the proper information from the information pool. The other action is to share and exchange owned information with others online and offline. Although some studies noted the negative effects of an individual’s information actions, such as misleading by misinformation, information overload and avoidance, anxiety and worry, (Soroya et al., 2021), there is a consensus that an individual’s information actions are significant and could benefit her/his a lot while dealing with COVID-19 crisis (Granderath et al., 2021; Kim & Hong, 2021; Pan et al., 2020).

To sum up, two kinds of actions that are referred to as online preventive actions and offline preventive actions against COVID-19 in this study that individuals may adopt. The online preventive actions aim to acquire, seek, and transmit information about COVID-19. The offline preventive actions are various activities, including wearing a mask, kee** social distance, and concerning personal hygiene, that individuals implement to protect themselves directly from COVID-19 epidemic.

Through conducting the online information behaviors, individuals on the one hand could increase their knowledge and awareness of the disease (Sørensen et al., 2012) and reduce uncertainties. On the other hand, individuals are capable of acquiring about preventive methods, current developments, policies, and regulations related to COVID-19, which may assist them to obtain measures to address or solve COVID-19-related problems (Kim & Hong, 2021; Tang et al., 2021). The consequences of an individual’s online information actions have an impact on her/his actual offline preventive actions. Liu (2020) indicated that an individual’s information seeking through digital media promotes her/him to implement practical preventive behaviors such as washing hands, staying social distance, and wearing facemasks. Lee and You (2021) found that people especially females and elders have a higher likelihood to adopt preventive actions when they read text messages about COVID-19. Farooq et al. (2020) noted that online searches for information related to COVID-19 had a significant impact on risk perception and response perception. As a result, we may believe that an individual’s online informational actions have a positive impact on her/his offline preventive actions and thus propose:

H1

Individuals’ online information actions of preventing COVID-19 positively influence her or his offline preventive actions.

The effect of situational motivation on individual preventive actions

This study discusses and analyzes how individuals’ motivations influence their online and offline preventive actions against COVID-19 by drawing on STOPS theory (Kim & Grunig, 2011) and self-concern and other-orientation theory (De Dreu, 2006; De Dreu & Nauta, 2009).

The STOPS theory was extended from the Situational Theory of the Public (STP) (Grunig, 1997, 2003) which explained why and predicted when individuals stay passive or active communication behaviors in facing a problem (Aldoory & Sha, 2007). The STOPS theory has been employed in multiple contexts such as health communication (Chon & Park, 2021; Kim & Hong, 2021; Kim & Lee, 2014), crisis communication (Jiang et al., 2019; Liu et al., 2019), and racial communication (Lee et al., 2022) to explore why and how people become active in communicative behaviors. The communication behaviors in STOPS include three dimensions: information acquisition, information selection, and information transmission. Information acquisition refers to the varying degrees of information-foraging that people do to solve problems. Information selection is defined as selective processing, interpretation, and propagation of information (Kim et al., 2010). Information transmission including information forwarding and information sharing refers to the desire of an individual to provide and disseminate his/her perception of a problem and the preferred method of solving it to other communicators (Kim & Grunig, 2011).

Regarding the three information behaviors, we focus on the two behaviors that are information acquisition and information transmission in this study. The major reasons for this are: firstly, information acquisition and information transmission are the actions that individuals are capable and are more likely to conduct during the COVID-19 epidemic (Chon & Park, 2021; Kim & Lee, 2014). Moreover, these two information actions could bring individuals benefits more directly than the action of information selection (Liu et al., 2019; Montesi 2021; Zimmerman, 2021). In addition, we think that individuals would evaluate and select information more or less in the process of acquiring and transmitting information online. Secondly, this study looks into the citizens in the Chinese cities which have infected cases in the post-epidemic era. The information related to COVID-19 mainly released by the government, public health sectors of China that would strictly supervise information launching and forecasting online. As a consequence, these authorities play a dominant role in influencing what information individuals would receive and thus leave little room for individual citizens to choose information. Thirdly, the components of STOPS framework employed in this study can be adjusted according to research contexts and problems. In addition, it is unnecessary to include all of components in the proposed model. For example, Kim and Lee (2014) examined the effects of two active information behaviors, i.e., information seeking and information forwarding, from the dimensions of information acquisition and information transmission on co** outcomes and processes in patients with chronic illness. Chon and Park (2021) checked individuals’ communication behaviors of acquiring and transmitting CDC information during COVID-19 based on the STOPS theory. Liu et al. (2019) integrated variables from the social-mediated crisis communication model and risk-specific variables into the STOPS model to examine public crisis communication and non-communication behaviors in the context of tornadoes.

Specifically, information acquisition in this study refers to obtaining information about COVID-19 in casual conversations with others or searching for relevant information online. Information transmission in this study depicts that individuals actively provide or forward information about COVID-19, or passively share their opinions with others. In line with (Jiang et al., 2019; Kim & Hong, 2021; Kim & Grunig, 2011; Liu et al., 2019), this study integrates these two specific information actions together and names online preventive actions. Moreover, we regard individual online preventive actions as a second-order construct that combines the two variables that are information acquisition and transmission in our proposed theoretical model.

As a difference from STP, the STOPS introduced the construct of situational motivation that is highlighted to drive individuals to adopt communicative behaviors purposefully to tackle a problematic situation (Kim & Grunig, 2011). Situational motivation in problem solving indicates the extent to which people stop to think about, remain curious about, and want to learn more about a problem. Kim and Grunig (2011) argued that individuals tend to take actions when they are situationally motivated to solve an issue or a problem as they become curious about and want to understand the problematic situation better. This situation-specific need is often positively associated with communicative actions in problem solving, owing to its goal-oriented nature (Kim & Grunig, 2011; Ni & Kim, 2009). The COVID-19 epidemic is still one of big problems that affect individuals’ life, work, and study. Although individuals have recognized the importance of solving the COVID-19 problem, they still cannot effectively fight the epidemic due to the lack of understanding and solutions to the epidemic. Therefore, they begin to be curious about the epidemic and think about how to stop it. This curiosity and thinking will inspire them to work hard to obtain solutions. Conduction of information behaviors including acquiring, forwarding, and sharing information related to COVID-19 is an important approach for individuals to understand the epidemic and to obtain proper preventive solutions. So we believe that situational motivation positively affects individuals’ online preventive actions. This paper proposes the following hypothesis:

H2

Individuals’ situational motivation positively influence their online preventive actions in the COVID-19 outbreak.

Furthermore, according to the STOPS theory, individuals’ perceptions of the situation including problem recognition, involvement recognition, and constraint recognition could activate their situational motivation. Thereinto, problem recognition refers to one’s perception that something is missing and that there is no immediately applicable solution to it (Kim & Grunig, 2011). Individuals who view COVID-19 as a public health problem realize that current measures still cannot fully address it and need to continuously explore the solutions. Involvement recognition indicates that an individual’s perception of what is relevant to a particular problem situation (Kim & Grunig, 2011). Understanding an individual’s level of involvement predicts how she/he may act in the face of problems, issues, and ideas. Finally, constraint recognition is individuals’ perceptions of obstacles that prevent them from taking actions to address the problem (Kim & Grunig, 2011). When individuals recognize the COVID-19 problem and its impact on themselves or others and believe that they have the capabilities of addressing the problem, they would enter the state of situational motivation in problem-solving. Thus, situational motivation in problem-solving, as the consequence of problem, constraint, and involvement recognition, sums up the effect of individuals’ perceptions and is a predictor of the individuals’ activeness (Chon & Park, 2021; Kim & Hong, 2021; Kim & Grunig, 2011).

Our study expects that the three perceptual variables will influence individuals’ situational motivation as reported in STOPS health issues literature to explain individual communicative actions in problem-solving (Jiang et al., 2019; Kim & Hong, 2021; Liu et al., 2019). In the context of the COVID-19 pandemic, individuals’ problem recognition (i.e., the perception that the outbreak would cause a serious threat to them and society) and involvement recognition (i.e., the perception that the outbreak is highly relevant to them) would motivate them to undertake efforts to solve the problem. In contrast, constraint recognition (i.e., the perception that laypersons like themselves face obstacles and possess limited ability to improve the situation) would discourage their motivation. Thus, we propose a set of hypotheses as follows.

H3a

Individuals’ problem recognition positively influences their situational motivation in the COVID-19 outbreak.

H3b

Individuals’ involvement recognition positively influences their situational motivation in the COVID-19 outbreak.

H3c

Individuals’ constraint recognition negatively influences their situational motivation in the COVID-19 outbreak.

The effect of concern-for-self and concern-for-others motivation on individual preventive actions

Aside from the key factors extracted from the original STOPS framework, this study introduces concern-for-self and concern-for-others as the social motivation that influence individual preventive actions during the COVID-19 epidemic.

The two motivations are extracted from the theory developed by (De Dreu & Nauta, 2009) who proposed two constructs that are self-concern and other-orientation. Specifically, self-concern may be understood as the tendency of one’s behaviors are to protect and improve self-interest, whereas other-orientation is geared towards the needs and interests of others, highlighting the importance of taking care of the weak and poor (De Dreu, 2006; De Dreu & Nauta, 2009). For self-concern and other-orientation, some scholars believe that the two belong to one concept, the two extremes of a single continuum (Bolino & Grant, 2016; De Dreu & Nauta, 2009). However, we think that self-concern and other-orientation are not a continuum; instead, they are a set of different dimensions that can be used to do categorical research from both self and other perspective, respectively. Crocker and Canevello (2012, 2015) argued that people are in two systems, the egosystem and the ecosystem. In the egosystem system, people are driven by a focus on what makes their needs satisfied; in the ecosystem system, decisions and behaviors people make are influenced by the people they care about. In earlier studies, the difference between concern-for-self and concern-for-others was distinguished and applied in the study of leadership (Blake & Mouton, 1964) and dispute resolution (Rubin et al., 1994), which showed how these motives drive leader behavior and conflict management alone and in combination. Furthermore, Thompson and Simkins (2017) studied the effect of two forgiveness motives, i.e., self-oriented and other-oriented, on the quality of superior-subordinate relationships; Tang et al. (2017) classified CEO values into self-enhancing and self-transcending value and then inspected the impact of both values on firm performance.

Based on self-concern and other-orientation theory (De Dreu, 2006; De Dreu & Nauta, 2009), we divide social motivation into concern-for-self and concern-for-others motivation. Specifically, concern-for-self motivation refers to the major purpose of an individual’s actions is to protect and improve her/his interests in the face of adverse external influences or threats. Concern-for-others motivation is oriented to the needs and interests of others, emphasizing one’s active actions are to protect others.

The two motivations are a state and susceptible to external influences. The interactionist view held that an individual’s perception of a situation affects her/his motivation and then subsequent behavior (Blass, 1984). Furthermore, there are studies that have shown that the stimulation of an individual’s concern-for-self motivation and concern-for-others motivation is affected by her/his perception of the situation (Bobocel, 2013; Crocker & Canevello, 2015; De Dreu et al., 2008). The difference in perception affects the strength of these two motivations (Abu-Tayeh et al., 2018; Baranik et al., 2022; De Dreu et al., 2008). In addition, stronger self-concern leads people to focus their information processing on self-serving cues, while stronger other-orientation leads them to group-related cues (De Dreu et al., 2008; Nijstad & De Dreu, 2012).

During the COVID-19 pandemic, we learned about COVID-19 through online technologies, news reports, or interpersonal communication that reported on the dangers of the pandemic (e.g., mortality, infection rates, economic losses, etc.), the mutation of the virus, the development of the epidemic, etc. With these accessed information, individuals realized the seriousness of the epidemic problem and the threats it posed. They are starting to think about how to protect themselves and their families from the adverse impact of the epidemic. Moreover, reading about the negative impact of the pandemic on others may also inspire people to care about others. Therefore, we believe that the individuals’ three situational perceptions of COVID-19 will stimulate the concern-for-self and concern-for-others motivation. Based on the above analysis, the following hypotheses are proposed:

H4a

Individuals’ problem recognition will positively influence their concern-for-self motivation in the COVID-19 outbreak.

H4b

Individuals’ involvement recognition positively influences their concern-for-self motivation in the COVID-19 outbreak.

H4c

Individuals’ constraint recognition negatively influences their concern-for-self motivation in the COVID-19 outbreak.

H4d

Individuals’ problem recognition positively influences their concern-for-others motivation in the COVID-19 outbreak.

H4e

Individuals’ involvement recognition positively influences their concern-for-others motivation in the COVID-19 outbreak.

H4f

Individuals’ constraint recognition negatively influences their concern-for-others motivation in the COVID-19 outbreak.

It has been found that concern-for-self and concern-for-others motivation drive individuals’ information seeking, processing, and retrieval while facing a problem that is required to make decisions or take actions (De Dreu & Nauta, 2009; De Dreu et al., 2008; Nijstad & De Dreu, 2012). The motivated group information processing model proposed by De Dreu et al. (2008) assumed that an individual preference for the distribution of outcomes between oneself and other group members (i.e., proself motivation and prosocial motivation) drives the kind of information group members attend to, encode, and retrieve. Nijstad and De Dreu (2012) argued that individuals with a prosocial motivation are assumed to process information to foster collective outcomes (such as group harmony, fairness, and high-quality collective decisions), whereas individuals with a proself motivation are assumed to process information to foster their outcomes (such as personal power or gains or letting other members do the hard work). Thus, these two motivations drive them toward biased information processing to foster group and/or individual goals.

Based on the above discussion, we believe that during the COVID-19 outbreak, individuals affected by concern-for-self motivation will actively take online preventive actions to protect themselves and their interests. Likewise, individuals affected by concern-for-others motivation will actively acquire and transmit information related to COVID-19 to protect others and maintain social stability. Thus, we argue that these two motivations will arise simultaneously and have an impact on the individuals’ online preventive actions and thus propose the following hypothesizes:

H5a

Individuals’ concern-for-self motivation positively influences their online preventive actions in the COVID-19 outbreak.

H5b

Individuals’ concern-for-others motivation positively influences their online preventive actions in the COVID-19 outbreak.

The concern-for-self and concern-for-others motivation not only impact individual information processing tendencies but also individual actual behaviors (Abu-Tayeh et al., 2018; Campos-Mercade et al., 2021; Jordan et al., 2021; Oreg & Nov, 2008; Ospina et al., 2021). Regarding behaviors of contributors in open-source projects, Oreg and Nov (2008) found that individuals who contribute to software development place more emphasis on self-concern motivation such as reputation building and self-development, while content contributors concern with hel** others more. Abu-Tayeh et al. (2018) examined the effects of both self-concern and other-orientation motivation on voluntary citizenship reporting, and demonstrated that these two motivations are all important, but self-concern motivation has a stronger impact than other-orientation motivation. In addition, some studies have demonstrated that prosocial motivations predict people’s willingness to practice behaviors such as social distancing and wearing face coverings. Ospina et al. (2021) indicated that compassionate goals predict individual COVID-19 preventive behaviors through three mediated reasons which are protecting the self, close others, and distant others. Moore et al. (2022) found that hesitant adopters would be willing to get the COVID-19 vaccine to protect their community, family, friends, or health security.

Therefore, we believe that concern-for-self and concern-for-others motivation which can be specified as to protect themselves and their families, or to reduce the harm of COVID-19 to others possibly promote an individual’s offline preventive actions. So, we propose the following hypotheses:

H6a

Individuals’ concern-for-self motivation positively influences their offline preventive actions in the COVID-19 outbreak.

H6b

Individuals’ concern-for-others motivation positively influences their offline preventive actions in the COVID-19 outbreak.

Based on the above analysis, we propose the research model that is presented in Fig. 1.

Fig. 1
figure 1

Research model

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Research methodology

Sampling and participants

To test the aforementioned hypotheses, we conducted an online survey in August 2022. During this period, only a part of provinces in China have COVID-19 infected cases. Since the purpose of this study is to investigate motivations of individuals to adopt preventive actions against COVID-19, we chose the individuals in the COVID-19 outbreak regions to participate in our survey. Those individuals are likely to concern COVID-19 and thus are inclined to adopt the preventive actions.

By using “Sojump”, a popular and widely used tool for surveying, our survey was sent to the individuals in the Chinese cities including Zhejiang, Henan, Chongqing, Hainan, Bei**g, Shanghai, and Guangdong. We collected a total of 726 questionnaires and excluded 98 invalid questionnaires that response time was too short, missed some questions, and had the same answers for all questions. Finally, we got 628 valid and completed responses for our study with a response rate of 86.50%.

Participants on average aged 31 (SD = 6.498). Females made up the majority of the sample (n = 364, 57.96%). The vast majority of participants were well educated, with 528 (84.08%) participants holding a bachelor’s or master’s degree. Table 2 shows the profiles of individual respondents.

Table 2 The profiles of the respondents
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Measures

To develop our survey measures, we adopted the existing valid scales wherever possible. When necessary, items were adjusted to be more suitable to the research context and questions of this study. For each item in the survey, we employed a five-point Likert scale where 1 = strongly disagree and 5 = strongly agree to capture respondents’ answers. An overview of items can be found in Appendix A.

To assess the situational perception variables including problem recognition, involvement recognition, and constraint recognition, we adapted scales from (Chon & Park, 2021; Kim & Hong, 2021; Kim & Grunig, 2011; Liu et al., 2019), but with minor modifications to make measurements applicable in the context of COVID-19.

To measure individual situational motivation, we developed three items by referring to (Kim & Grunig, 2011; Lee et al., 2022; Liu et al., 2019) to represent the level of concern and curiosity of individuals about COVID-19.

The measures of concern-for-self and concern-for-others motivation were mainly adapted from (Baranik et al., 2022; De Dreu, 2006; De Dreu & Nauta, 2009; Tang et al., 2017). Specifically, concern-for-self consisted of two items and concern-for-others was measured with four items.

Individuals’ online preventive actions consisted of two information behaviors, i.e., information acquisition and transmission, which were measured by the scales adapted from (Chon & Park, 2020; Kim & Hong, 2021; Kim & Grunig, 2011; Liu et al., 2019). More specifically, information acquisition was measured by seven items that examine what information and how they acquire about COVID-19. A six-item scale was used to measure information transmission to examine how individuals transmit or share information about COVID-19.

To assess individuals’ offline preventive actions, we adapted scales from (Breakwell et al., 2021; Liu, 2020; Nelson-Coffey et al., 2021; Ospina et al., 2021) which focused on individual preventive behaviors against COVID-19. We finally established four items which indicates the predominant and routine actions that individuals are capable to implement during the COVID-19 epidemic to measure this variable.

Data analysis

We analyzed the data using the Partial Least Squares Structure Equation Model (PLS-SEM) and SmartPLS 3.0. PLS-SEM is more suitable for research testing when the research goal is to better understand the increasing complexity by exploring theoretical extensions of existing theories (Hair et al., 2019; Rigdon et al., 2017). Different from the traditional SEM which can only construct a reflective structural model, both reflective measurement models and formative measurement models can be constructed in PLS-SEM model (Hair et al., 2017). In addition, when the structural model under test is complex, including many constructs, indicators, and/or model relationships, it is more appropriate to use the PLS-SEM method (Hair et al., 2019). The superiority of PLS-SEM has been demonstrated in handling small samples (Hair et al., 2017; Rigdon et al., 2017), but PLS-SEM can still take advantage of its data processing in large data samples (Akter et al., 2017; Hair et al., 2019; Sarstedt et al., 2016).Therefore, we chose PLS-SEM to validate our hypotheses according to our research context and model.

This study followed the guidelines by Hair et al. (2017) for evaluation and reporting results to conduct the PLS-SEM analysis with two steps. First, the measurement model was evaluated by checking the reliability and validity of the measurement terms for all variables to ensure the quality of the scale we use. Secondly, the structural model was evaluated using the path coefficient (β) to examine the relationship between the structures. Due to the small data set for such analyses, we calculated the bootstrap confidence intervals to assess the statistical significance of the effect by running the full bootstrap** process across 5000 samples with no significant change at a significance level of 0.05.

Results

Validity of the scales

Table 3 reported the reliability and validity of the scale. Reliability reflects consistency between items that measure the same structure. Reliability was tested using Cronbach’s alpha and composite reliability values.

Table 3 Reliability test for scales
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As shown in Table 3, Cronbach’s alpha values were greater than 0.6 and composite reliability values were greater than 0.7, the factor loadings of each potential variable in this study were greater than 0.6, which met the requirements of convergent validity (Chen & Tsai, 2007; Ertz et al., 2016; Truong et al., 2011). For the value of AVE, according to Hu and Bentler (1998), if AVE value is greater than 0.4, it should be taken as evidence of convergent validity. Fornell and Larcker (1981) argued that if AVE value is less than 0.5, but the composite reliability value is greater than 0.6, the convergent validity of the construct is acceptable. The above conclusions were adopted in studies (Elprama et al., 2020; Hu et al., 2023; Kement et al., 2022; Lam, 2012; Malhotra, 2010). According to the calculation results presented in Table 3, all AVE values were greater than 0.4 and all constructs had composite reliability values greater than 0.7, demonstrating that the convergent validity of the construct in our model is acceptable.

Table 4 showed the discriminant validity of the scale. The diagonal elements in the table are the square roots of the AVE values and the off-diagonal elements are the squared correlations among factors. Discriminant validity is the degree to which items distinguish between constructs. We evaluate discriminant validity by comparing the square root of AVE of each structure and its correlation to other structures. The results showed that the square root of AVE value of each structure was higher than its correlation with any other structures (Fornell & Larcker, 1981; Hair et al., 2017), indicating satisfactory discriminant validity of the scale.

Table 4 Discriminant validity testing
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Common method variance testing

Before proceeding with the structural analyses and examining the hypothesized model, we tested for the presence and impact of common method variance (CMV) effects in our data (Podsakoff et al., 2003). We reduced the impact of CMV on the results of this study through both procedural control and statistical control. In terms of procedural control, we followed the control strategy of MacKenzie and Podsakoff (2012). First of all, we referred to some prior related studies in designing the questionnaires, and adapted the content of the topic according to the actual situation to match the difficulty of the topic with the ability of the interviewees. Second, we considered the layout of the question items to separate the independent and dependent variables in order to balance the order of the questions. Finally, we provided some rewards to the interviewees to increase their response motivation. In terms of statistical control, we used Harman’s single-factor approach for CMV testing (Podsakoff et al., 2003). The results of the exploratory factor analysis of 34 question items showed that there were 7 factors with eigenvalues greater than 1 and 26.653% of the first-factor variance (< 50%), indicating that there was no serious CMV in this study.

Hypotheses testing

We used the standard bootstrap procedure in SmartPLS on 5000 bootstrap** samples to assess significance of the paths of structural model. The calculation results are shown in Table 5; Fig. 2, respectively.

Table 5 Hypotheses testing
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Hypothesis 1

examines the relationship between online and offline preventive activities. The analysis result (i.e., β = 0.178, p < .001) indicated that individuals’ online preventive actions affect their offline preventive actions positively and significantly. H2 predicted a positive association between situational motivation and individuals’ online preventive actions, and it was supported (β = 0.450, p < .001). Hypotheses H3a to H3c addressed the associations among the variables derived from the original STOPS framework. Corresponding to the STOPS contentions, situational motivation was positively associated with problem recognition (β = 0.374, p < .001) and involvement recognition (β = 0.199, p < .001), but negatively with constraint recognition (β=-0.286, p < .001), so hypothesis H3a, H3b, and H3c was supported respectively.

Hypotheses H4a to H4f proposed the influence of three situational perceptions (i.e., problem recognition, involvement recognition, and constraint recognition) on concern-for-self and concern-for-others motivation, respectively. The analysis results showed that concern-for-others motivation was positively affected by problem recognition (β = 0.249, p < .001), involvement recognition (β = 0.210, p < .001), and negatively affected by constraint recognition (β=-0.370, p < .001). Thus, H4d to H4f were supported. The concern-for-self motivation was influenced positively by problem recognition (β = 0.470, p < .001) and involvement recognition (β = 0.138, p < .01), and was not significantly associated with constraint recognition (β=-0.033, p = .341). So, H4a and H4b were supported but H4c was not supported. The results for both motivations for individuals’ online and offline preventive actions were as follows: the concern-for-others motivation (β = 0.349, p < .001) has a positive effect on individuals’ online preventive actions while the concern-for-self motivation (β = 0.006, p = .870) has no significant effect. Consequently, hypothesis H5a was not supported and hypothesis H5b was supported. Regarding individual offline preventive actions, the study confirmed a positive effect of both concern-for-self (β = 0.415, p < .001) and concern-for-others (β = 0.189, p < .01) motivation, which supported H6a and H6b.

Fig. 2
figure 2

Structural model results

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Discussion

The purpose of this study is to investigate the motivational factors that influence individual online and offline preventive actions against COVID-19. Using STOPS theory as the research framework (Kim & Grunig, 2011) and combining self-concern and other-orientation theory (De Dreu, 2006; De Dreu & Nauta, 2009), we mainly shed light on three aspects: first, we verified the relationship between online and offline preventive actions; second, we examined the impact of situational motivation and concern-for-self and concern-for-others motivation on individual preventive actions; finally, we explored the effects of situational perception variables on the three motivations.

Individuals’ online and offline preventive actions in the COVID-19 context

Fishbein and Cappella (2006) argued that individuals’ perceptions and behaviors related to health risks are likely to be affected by the messages they are exposed to during a crisis event or outbreak. Moreover, message receipt can increase beliefs that will ultimately promote healthy behaviors. In the meantime, previous studies have reported that information consumption on social media during a crisis can boost individuals’ offline preventative behaviors such as self-isolation, washing hands, and receiving vaccinations (Farooq et al., 2020; Kim & Hawkins, 2020; Lee et al., 2022; Liu, 2020). Our research confirmed that individual online preventive actions have a positively predictive effect on offline actions in the COVID-19 outbreak.

Information needs tend to increase in the times of trauma, and individuals use online technologies (i.e., social media, websites, and apps) to fulfill this unmet need and exchange information with others during infectious disease outbreaks (Yoo et al., 2016). By acquiring and transmitting information about COVID-19, individuals not only increased awareness of the pandemic but also gained access to measures of combating COVID-19. This awareness reduces uncertainty in the face of the pandemic (Granderath et al., 2021), and people can combine the solutions available to the current situation and act promptly to respond to the COVID-19 outbreak. Such results remind government advocacy departments and public health workers of the need to ensure that accurate health information is disseminated online (Kim & Hawkins, 2020; Tang et al., 2021). Meanwhile, individuals are likely to share their gained information, resulting in a suggestion that public health agencies need to take a more proactive approach to make sure the information online is accurate and worth spreading to others.

STOPS in the COVID-19 context

The STOPS theory was used to predict an individual’s motivation to solve a problem or issue, as well as their communicative behaviors about a problem or issue (Kim & Grunig, 2011). Consistent with previous studies using STOPS (Chon & Park, 2020, 2021; Jiang et al., 2019; Kim & Hong, 2021; Liu et al., 2019), individual problem recognition and involvement with COVID-19 are positively correlated with situational motivation, while individual constraint recognition of situational is negatively correlated with situational motivation. In addition, individuals’ situational motivation to handle COVID-19 problem is positively correlated with their online preventive actions. These results suggested that individuals were motivated to access information about the pandemic when they see COVID-19 as a problem and believe they are affected by it and feel empowered to address it.

For public relations professionals especially government communications officers, these findings underscore the importance of pandemic information communication so that individuals can prepare for the COVID-19 outbreak. Specifically, they can help individuals to take COVID-19 seriously, recognize its potential impacts, and review their capabilities. In the meantime, through effective informational communication interventions, individuals can better communicate how to mitigate and prepare for pandemic risks. Additionally, when there are updates of the COVID-19 outbreak, it is necessary for them to timely report on the scope of the outbreak and transmission trends.

Concern-for-self and concern-for-others motivation in the COVID-19 context

The present study introduced concern-for-self and concern-for-others motivation in the STOPS framework to show how key variables in the tested model affect individuals’ preventive behaviors in offline settings. It enriched existing STOPS studies that typically focused on individuals’ online information behaviors.

We found that the two individual motivations as a state rather than a trait were influenced by external situational factors. Specifically, the more awareness of the problems of COVID-19 (i.e., problem recognition) and their negative impacts (i.e., involvement recognition), the more likely individuals are to be awakened to the motivation to protect themselves or help others. However, our findings demonstrated that the level of constraint recognition was only negatively correlated with the individuals’ concern-for-others motivation, and did not prove its significant effect on concern-for-self motivation. Due to successive outbreaks of the pandemic and the continuous evolution of the virus, individuals are encountering increasing obstacles in improving the COVID-19 situation, but the ability of individuals to cope with the epidemic has not grown in tandem, which may cause individuals to struggle to cope with the problems caused by COVID-19, thereby reducing the individual’s concern for others. However, they first do what they think is good for them in facing the risk of COVID-19 because the individuals are fundamentally self-interested (Jordan et al., 2021; Lake et al., 2021; Miller, 1999). Therefore, even if many difficulties are encountered, people will not give up protecting their lives and interests.

Online preventive actions can enable individuals to get relevant information to understand how things are unfolding. Meanwhile, individuals also are required to take offline actions to protect themselves directly (Liu et al., 2019). Our findings demonstrated that concern-for-others motivation has a positive effect on individual preventive actions against COVID-19, both online and offline, but concern-for-self motivation only has a positively predictive effect on offline actions. Although the concern-for-self and concern-for-others motivation could encourage individuals to actively adopt offline actions such as wearing a mask and washing hands frequently, which is line with the findings of (Campos-Mercade et al., 2021; Ospina et al., 2021). However, the concern-for-self motivation (β = 0.415, p < .001) has a greater impact than the concern-for-others motivation (β = 0.189, p < .001) on individual actual preventive actions. It noted that concerns about an individual’s health, needs, and interests are more likely to motivate them to act accordingly because it tends to be habitual, automatic, and often unconscious (De Dreu & Nauta, 2009). In addition to caring about satisfying their own needs and desires, people also have the capacity for empathy, compassion, and generosity that is motivated by concern for the well-being of others (Mikulincer & Shaver, 2010).

Individuals can care for and help others not only by taking practical actions but also by participating in online activities (Chon & Park, 2021; Lee et al., 2022). Research findings on the impact of social motivations on online preventive actions show that individuals who pay more attention to others are more willing to help others by acquiring, transmitting, and sharing information about COVID-19. With the advent of digital media, an individual can help more people through online actions than offline, thereby achieving the goal of protecting others (Kim & Hawkins, 2020; Liu, 2020).

For the above results, we believe that how individuals perceive and evaluate the situation is crucial to guide them into COVID-19 preventive actions. These social motivations are an important predictive mechanism that translates an individual’s perceived severity of problems and perceptions of self-ability into her/his participation activities, suggesting that an individual’s actions occur based on context-specific evaluations.

Conclusion

The solution to public health problems usually requires the active participation of individuals to acquire sufficient knowledge and perform appropriate behaviors. How motivate individuals to take actions becomes the key to problem solving. In the COVID-19 pandemic context, understanding the individuals’ motivations to adopt COVID-19 preventive actions will serve as a starting point for addressing the COVID-19 epidemic. Based on the STOPS theoretical framework and self-concern and other-orientation theory, this study shed light on how motivations including situational motivation, concern-for-self, and concern-for-others motivation and their antecedent situational perception factors affect individual online/offline COVID-19 preventive actions. The findings demonstrated that the framework proposed in this study can be applied to predict and explain individuals’ online and offline preventive actions in the COVID-19 crisis. More specifically, this study focused on individual online and offline preventive actions that all play a critical role in preventing COVID-19 and further verified the positive influence of online preventive actions on offline actions. Furthermore, the research results verified the applicability of the STOPS framework in explaining individual preventive actions especially online actions. This study incorporated the motives of concern-for-self and concern-for-others in the STOPS framework and further confirmed their roles in stimulating individual preventive actions. It not only helps to extend the previous STOPS literature but also contributes to understanding comprehensively what motivates individual preventive actions online and offline in public health crises.

This study also suffers a few limitations. First, because we used the sample service provided by the “Sojump”, as with other survey studies using online panels such as Qualtrics, we did not have sufficient control over the environment in which participants took the survey. Although regional source restrictions were set, the coverage of selected regions is still not comprehensive, so the richness of the data sample still needs to be enhanced. Second, the present study combined self-concern and other-orientation theory with STOPS and used them in the context of COVID-19, the measures of self-concern and other-orientation may not have been considered comprehensively. Therefore, more comprehensive multi-item measures reflecting concern-for-self and concern-for-others motivation are needed in future studies. Finally, when examining individuals’ online preventive actions, this paper analyzed only two dimensions, i.e., information acquisition and information transmission, and treated information behaviors as a unidimensional concept in the analysis. As a result, this study did not specifically analyze whether the three motivations studied in this paper have different effects on the two information behaviors respectively. Subsequent studies can analyze in depth the effects of the motivations on different information behaviors.