At the beginning of 2020, the disease caused by a novel coronavirus spread rapidly around the world. To control the spread of COVID-19, people were asked to stay at home and keep distance from others. Even so, as shown in the real-time data of John Hopkins University, by January 18, 2022, there were over 330 million confirmed cases globally.

Since the beginning of this outbreak, the Chinese government has provided daily updates about surveillance and confirmed cases on websites and social media to emphasize the need for prevention [1]. A survey conducted by the Chinese Academy of Social Science showed that many people in China spent a lot of time searching and reading COVID-19-related media content per day [2]. Social media is a group of Internet-based applications that allow the creation and exchange of user-generated content [3]. And social media engagement usually represents users’ interactions with the content, including views, likes, comments, shares, and postings [4]. But a high level of disaster-related media engagement would cause public panic and mental health problems [5].

According to the conservation of resources theory, individuals’ awareness of the loss of valued entities (such as objects, personal characteristics, conditions, and energies) would lead to negative psychological outcomes [6]. A previous experiment had proved that exposure to a video clip depicting terror attacks could increase individuals’ levels of the perceived threat and negative affect [7]. As for the current COVID-19 pandemic, it is a threat to all the people around the world. And media content of this life-threatening event makes people think about their inevitable death [8], thus leading to feelings of helplessness and lowering one’s sense of meaning in life and satisfaction with life [7].

Previous empirical studies had found that viewing negative disaster-related content was associated with negative psychological outcomes, such as increases of depression [9], anxiety [10], stress [11], and death anxiety [12]. And people who frequently reading COVID-19-related media content had more COVID-19-related anxiety symptoms than those who had less media exposure [13]. However, some recent studies found that compared with negative content, positive ones have opposite results. Content like hero acts and information about the disaster itself was associated with increases of positive affect [14] and lower odds of post-traumatic stress disorder [15].

Generally, postings and views are two kinds of media engagement. Views are private engagement by viewing social media posts or videos, while postings are spreading content through public sharing into public networks or platforms [4]. Therefore, they are two completely distinct kinds of behaviors. However, previous studies mostly focused on exploring relationships between viewing the disaster-related media content and psychological outcomes, while ignoring the associations between posting behaviors and psychological outcomes. For example, LaRose et al. [16] indicated that individuals having higher levels of negative affect and stress would relieve these negative experiences by using social media. And according to the uses-and-gratifications theory, people have specific needs to be satisfied when using social media [17]. During the lockdown and home quarantine, their need may be social interactions. Therefore, it is conceivable that people could maintain social interactions with others by posting COVID-19-related content on their social media [18]. And these would increase support from their friends, which was good for mental health [19]. While people who did not post content on their social media did not take this advantage. Thus, the hypothesis of the present study was that people who posted COVID-19-related content would have fewer negative experiences than people who did not.

Furthermore, although many studies have already been conducted to determine whether different levels of disaster-related media engagement had different impacts on psychological outcomes, they only detected a few psychological outcomes at one time [5,13]. For example, a survey aimed to find out whether there were differences in anxiety and depression between the participants who had higher media engagement and those who had lower one by using logistic regression analyses [20]. Due to the limitation of traditional analysis methods (e.g., t-tests and analysis of variances), the relationships among many (more than five) variables cannot be clarified clearly at one time.

As mentioned above, many kinds of psychological outcomes were associated with disaster-related media engagement. Network analysis is particularly useful for visualizing complex relationships between many variables [21,22]. Previously, researchers mostly focused on describing the characteristics of nodes and edges in a single network generated from a single population. For example, a prior study investigated 196 adults with bulimia nervosa (BN). And then a correlation network was generated from these adults’ responses to identify the central symptoms of BN [23]. Recently, researchers’ focuses have shifted to compare the structure of the networks generated from different subpopulations [24].

Therefore, in the present study, first, participants were divided into two groups by their posting behaviors. Individuals who have posted COVID-19-related media content were in one group, and the remaining individuals without posting behaviors were in the other group. Then two networks were generated separately to examine the relationships between positive affect, negative affect, depression, anxiety, stress, satisfaction with life, death anxiety, and meaning in life. At last, network comparison tests were conducted to examine whether there were differences between those two networks.

Firstly, results of independent t-tests indicated that the Post group had lower levels of negative affect, anxiety, stress, and death anxiety. Then, the present study generated two networks for the Npost group and the Post group to depict the relationships between positive affect, negative affect, depression, anxiety, stress, satisfaction with life, death anxiety, and meaning in life. And network comparison tests were conducted to compare the differences between these two networks. Results showed that these two networks differed in global strength, two edges (meaning in life-positive affect and negative affect-anxiety), and node centrality indices. In the Npost group’s network, stress and depression were central nodes, while in the Post group’s network, negative affect was the central one.

The present study found that people who posted COVID-19-related content on their social media had lower levels of negative affect, anxiety, stress, and death anxiety. Being involved in a pandemic would certainly lead to negative psychological outcome [1,6], but individuals tended to relieve these negative feelings by using social media [16]. Previous research suggested that active social media use such as posting content was different from negative social media use which was just scrolling through news feeds or browsing photographs of friends. And results showed that active social media use could decrease negative experiences such as fatigue [53]. Additionally, although the difference in depression symptoms between these two groups was not significant, the mean score of the Post group was still lower than that of the Npost group. Besides, no significant differences were found in positive affect, satisfaction with life, and meaning in life between these two groups. One potential explanation was that during the lockdown or self-quarantine, people spent more time caring for family and their friends [54,55]. Thus, most of them felt more satisfied with their life.

In the Npost group’s network, stress had the highest strength and betweenness centrality and the second-highest closeness centrality, indicating that it was the central node. Consistent with other studies, the present study found stress, anxiety, depression, and negative affect were positively correlated with each other [14]. And stress was also negatively associated with satisfaction with life in the pandemic context in line with previous research under normal situations [56,57], but this negative relationship was weak. Depression was also a central node, having the highest closeness centrality and the second-highest strength and betweenness centrality. And consistent with previous studies, it was negatively correlated with positive affect and meaning in life [14,37,58]. Meaning in life is a psychological source for enhancing healthy coping [59], and it had a strong correlation with more positive wellbeing [60]. Thus, in the disaster context, the higher level of meaning in life would negatively correlate with depression and anxiety but positively correlate with satisfaction with life and positive affect. While anxiety had the lowest betweenness centrality and the third-highest strength and closeness centrality. Lower betweenness centrality and higher strength and closeness centrality indicated that anxiety was not the only node close to many other nodes, and it was not on the shortest path between the other nodes. That meant anxiety was not the central node of this network despite its higher strength and closeness centrality. And satisfaction with life, death anxiety, meaning in life, and positive affect had lower centrality indices, having fewer associations with other variables.

Compared with the Npost group’s network, negative affect had significantly higher closeness centrality in the Post group’s network. And it was the central node of the Post group’s network, having the highest betweenness and closeness centrality. Similar to the Npost group’s network, negative affect was related to anxiety and death anxiety in the Post group’s network. Surprisingly, it had a positive association with positive affect. Generally, people would think negative and positive affect naturally negatively correlated with each other. But indeed, these are two independent processes [61,62]. And the previous study had found that COVID-19-related media exposure was associated with increases of both negative and positive affect [14]. Stress had the highest strength centrality in the Post group’s network, but lowest betweenness centrality, indicating it lay on no shortest path between other variables. This was different from the Npost group’s network, where stress was the central node. But like the Npost group’s network, in the Post group’s network, satisfaction with life, death anxiety, and meaning in life were still at the edge. Furthermore, because the Post group’s network had higher global strength, each node in the Post group’s network had a higher strength centrality than that in the Npost group’s network. Especially for positive and negative affect, they were significant at the levels of α=0.05 and α=0.01. The potential explanation for this significant result may be that the weight of meaning in life-positive affect and negative affect-anxiety in the Post group’s network is significantly larger than that in the Npost group’s network.

There were still some limitations in the present study. First, this study was a cross-sectional design, so no causal relationship could be revealed. Although time-series data can be analyzed by using multilevel vector autoregressive time-series models to examine potential causal associations [63], data collection for this analysis method is very difficult [53,64]. Besides, network comparison tests are not developed for this kind of network. Secondly, the participants were not chosen at random, so the parameters of interest may vary from one sample to another [65]. And all the participants were from China, the generalization of conclusion for residents in other countries is still unexplored. Finally, some other psychological factors were also proved to be associated with the COVID-19 outbreak, but all these studies were published after the beginning of the survey, such as fear of COVID-19 [66] and intolerance of uncertainty [65]. So, these factors were not taken into consideration in the present study.

Nevertheless, the results of the present study indicated that the posting behavior on social media was related to decreases of negative affect, anxiety, stress, and death anxiety. And two networks for the Npost group and the Post group had different central nodes. The central nodes were stress and depression, for Npost network, while negative affect instead for Post network. Therefore, for individuals who posted COVID-19-related content on social media, more attention should be paid when having a higher level of negative affect to prevent comorbidities. While for individuals who did not post this content, pay attention to higher levels of stress and depression.