Protecting public’s wellbeing against COVID-19 infodemic: The role of trust in information sources and rapid dissemination and transparency of information over time

Abstract

Objectives
This study examined how trust in the information about COVID-19 from social media and official media as well as how the information was disseminated affect public’s wellbeing directly and indirectly through perceived safety over time.

Methods
Two online surveys were conducted in China, with the first survey (Time1, N = 22,718) being at the early stage of the pandemic outbreak and the second one (Time 2, N = 2,901) two and a half years later during the zero-COVID policy lockdown period. Key measured variables include trust in official media and social media, perceived rapid dissemination and transparency of COVID-19-related information, perceived safety, and emotional responses toward the pandemic. Data analysis includes descriptive statistical analysis, independent samples t-test, Pearson correlations, and structural equation modeling.

Results
Trust in official media, perceived rapid dissemination and transparency of COVID-19-related information, perceived safety, as well as positive emotional response toward COVID-19 increased over time, while trust in social media and depressive response decreased over time. Trust in social media and official media played different roles in affecting public’s wellbeing over time. Trust in social media was positively associated with depressive emotions and negatively associated with positive emotion directly and indirectly through decreased perceived safety at Time 1. However, the negative effect of trust in social media on public’s wellbeing was largely decreased at Time 2. In contrast, trust in official media was linked to reduced depressive response and increased positive response directly and indirectly through perceived safety at both times. Rapid dissemination and transparency of COVID-19 information contributed to enhanced trust in official media at both times.

Conclusion
The findings highlight the important role of fostering public trust in official media through rapid dissemination and transparency of information in mitigating the negative impact of COVID-19 infodemic on public’s wellbeing over time.

Full text

Frontiers in Public Health 01 frontiersin.org
Protecting public’s wellbeing
against COVID-19 infodemic: The
role of trust in information sources
and rapid dissemination and
transparency of information over
time
YingnanZhou
1,2, 3, AirongZhang
2, XiaoliuLiu
6, XuyunTan
4,
RuikaiMiao
7, YanZhang
3,4 and JunxiuWang
3,4, 5*
1 School of Sociology and Ethnology, University of Chinese Academy of Social Sciences, Beijing, China,
2 Health and Biosecurity, CSIRO, Brisbane, QLD, Australia, 3 School of Mental Health, Wenzhou Medical
University, Wenzhou, China, 4 Institute of Sociology, Chinese Academy of Social Sciences, Beijing,
China, 5 School of Psychology, Inner Mongolia Normal University, Hohhot, China, 6 Faculty of Ideological
and Political Education and Moral Education, Beijing Institute of Education, Beijing, China, 7 Mental
Health Education Center, Shijiazhuang Tiedao University, Shijiazhuang, China
Objectives: This study examined how trust in the information about COVID-19
from social media and ocial media as well as how the information was
disseminated aect public’s wellbeing directly and indirectly through perceived
safety over time.
Methods: Two online surveys were conducted in China, with the first survey
(Time1, N = 22,718) being at the early stage of the pandemic outbreak and the
second one (Time 2, N = 2,901) two and a half years later during the zero-COVID
policy lockdown period. Key measured variables include trust in ocial media
and social media, perceived rapid dissemination and transparency of COVID-
19-related information, perceived safety, and emotional responses toward the
pandemic. Data analysis includes descriptive statistical analysis, independent
samples t-test, Pearson correlations, and structural equation modeling.
Results: Trust in ocial media, perceived rapid dissemination and transparency
of COVID-19-related information, perceived safety, as well as positive emotional
response toward COVID-19 increased over time, while trust in social media and
depressive response decreased over time. Trust in social media and ocial media
played dierent roles in aecting public’s wellbeing over time. Trust in social media
was positively associated with depressive emotions and negatively associated
with positive emotion directly and indirectly through decreased perceived
safety at Time 1. However, the negative eect of trust in social media on public’s
wellbeing was largely decreased at Time 2. In contrast, trust in ocial media was
linked to reduced depressive response and increased positive response directly
and indirectly through perceived safety at both times. Rapid dissemination and
transparency of COVID-19 information contributed to enhanced trust in ocial
media at both times.
Conclusion: The findings highlight the important role of fostering public trust
in ocial media through rapid dissemination and transparency of information in
mitigating the negative impact of COVID-19 infodemic on public’s wellbeing over
time.
OPEN ACCESS
EDITED BY
Xue Yang,
The Chinese University of Hong Kong, China
REVIEWED BY
David Conversi,
Sapienza University of Rome, Italy
Gour Gobinda Goswami,
North South University, Bangladesh
Hui Zhang,
Nanjing Normal University, China
*CORRESPONDENCE
Junxiu Wang
casswjx@163.com
SPECIALTY SECTION
This article was submitted to
Public Mental Health,
a section of the journal
Frontiers in Public Health
RECEIVED 11 January 2023
ACCEPTED 27 March 2023
PUBLISHED 17 April 2023
CITATION
Zhou Y, Zhang A, Liu X, Tan X, Miao R,
Zhang Y and Wang J (2023) Protecting public’s
wellbeing against COVID-19 infodemic: The
role of trust in information sources and rapid
dissemination and transparency of information
over time.
Front. Public Health 11:1142230.
doi: 10.3389/fpubh.2023.1142230
COPYRIGHT
© 2023 Zhou, Zhang, Liu, Tan, Miao, Zhang and
Wang. This is an open-access article distributed
under the terms of the Creative Commons
Attribution License (CC BY). The use,
distribution or reproduction in other forums is
permitted, provided the original author(s) and
the copyright owner(s) are credited and that
the original publication in this journal is cited,
in accordance with accepted academic
practice. No use, distribution or reproduction is
permitted which does not comply with these
terms.
TYPE Original Research
PUBLISHED 17 April 2023
DOI 10.3389/fpubh.2023.1142230

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Frontiers in Public Health 02 frontiersin.org
KEYWORDS
psychological stress, trust, media sources, information dissemination, perceived safety,
wellbeing, information transparency
1. Introduction
COVID-19 has been constantly evolving since its outbreak in
early 2020. At the beginning, there was limited scientic understanding
and knowledge about the coronavirus. Due to the unknown nature of
the novel virus, misinformation and rumors were widely spread across
social media platforms, which instilled a strong sense of out-controlled
crisis (1–6). Over 2 years into the pandemic, scientic understanding
of COVID-19 has been advanced, and vaccines have been developed.
Protective measures such as wearing mask, sanitizing hands, and
keeping social distance have been commonly adopted in daily life,
which is regarded as a “new normal.” While the virus has been
constantly mutating, so were rumors and misinformation, especially
regarding the COVID-19 vaccines. For example, exaggeration of side
eects (e.g., infertility, chronic illness, mental illness) as well as distrust
in vaccine development (e.g., crucial trials skipped) were widespread
on social media, leading to vaccine hesitancy (7–13). Meanwhile, the
preventive measures and COVID-19-related policies taken by
governments were also changing over time and dierent from country
to country. While most of countries have reopened by early to
mid-2022, strict lockdown and COVID-zero policy were still in place
in China. Such misinformation and dierences in government policies
have kept sending confusing message to the public. is situation
highlights the remarkable characteristics of the concurrence of
virology and virality of COVID-19, where fast virus spreading is
coupled with rapidly spreading of information and misinformation
(14). Precisely as WHO Director-General Dr. Ghebreyesus pointed
out, “We’re not just ghting an epidemic; we are ghting an
infodemic” (15).
Extensive empirical studies from dierent countries have
demonstrated that a broad range of rumors and misinformation about
COVID-19 spread across social media, which negatively impacted
public’s wellbeing and posited challenge for pandemic control (1–7).
Research has shown that trust in COVID-19 information from social
media was negatively linked to accurate knowledge about COVID-19
(16), positively linked to beliefs in COVID-19 myths and false
information (17) as well as vaccine hesitancy (5, 18, 19). Moreover,
rumors and misinformation fueled fears and led to psychological
distress among the public over the course of COVID-19 pandemic
(20–29). Frequently using social media as an information source for
COVID-19 was signicantly related to poorer psychological wellbeing
(28, 30–32). Moreover, erroneous, inconsistent, unveried, and oen
conicting news and messages led to uncertainty, which caused
intense stress to the public (33). Emerging research indicates that
perceived vulnerability to COVID-19 mediated the relationship
between exposure to COVID-19 news and depressive symptoms (34).
In addition, when people used social media to obtain COVID-19-
related information, their perceived risk of being infected heightened
as the level of concern increased (35). In turn, higher risk perception
and lack of perceived safety toward COVID-19 led to increased
anxiety and depressive symptoms (36–39). ose ndings suggest that
the conicting information and uncertainty on social media made
people feel unsafe as it is not clear how to protect oneself. is led to
fear and stress, and hence, impacted wellbeing. However, how trust in
social media aect public’s wellbeing during COVID-19 pandemic,
and the mediating role of perceived safety are not yet directly
examined. Informed by the research reviewed above,
wehypothesized that:
H1: Trust in COVID-19-related information from social media
was negatively associated with positive emotional response and
positively associated with depressive emotional response toward
COVID-19.
H2: Perceived safety mediates the relationship between trust in
social media with positive and negative responses toward COVID-
19, respectively.
To minimize public fear and confusion caused by social media,
transparency and rapid dissemination of information by government
agencies has been suggested crucial (40–42). e role of transparency
and trust was also demonstrated in managing public fear and panic in
SARS outbreak in Singapore (43) as well as during other outbreaks
including Ebola in West Africa and MERS-CoV in South Korea (44).
Indeed, timely, accurate and transparent information from ocials is
foundational for the public to implement protective measures,
mitigate the negative impact of the pandemic, and to reduce
psychological distress in the crisis (45, 46). e satisfaction with
governments’ communication about COVID-19 was linked to public
trust in government (47, 48). ese ndings suggest that transparency
and rapid dissemination of information about COVID-19 is the key
factors to build public trust in ocial media. erefore,
wehypothesized:
H3: Perceived rapid dissemination and transparency of the
information about COVID-19 are positively related to trust in
ocial media.
With respect to how trust in ocial media would aect public’s
wellbeing, existing literature pointed to dierent directions. Some
studies indicated that ocial media in some countries applied a fear-
based communication strategy (e.g., showing realistic pictures and
giving direct information on COVID-19 death statistics) and
suppressed scientic debate to persuade public to adhere to
recommended health behaviors such as wearing mask, practicing social
distance, and getting vaccinations (49–52). Such fear-inducing
approach can increase levels of perceived threat, cause psychological
distress, and aect wellbeing among the public (51, 53–55). In this case,
trust in ocial media would negatively aect public’s wellbeing through
decreasing perceived safety from being infected. Meanwhile, other
studies suggested the opposite. ese studies found trust in the

Zhou et al. 10.3389/fpubh.2023.1142230
Frontiers in Public Health 03 frontiersin.org
government and obtaining information from ocial media reduced
perceived risk toward COVID-19, mitigated mental distress, and
improved psychological wellbeing among the public (35, 56–58). ese
ndings suggested that receiving information from trusted and
authoritative source would give people certainty and ecacy, hence,
increasing perceived safety and enhancing mental wellbeing. In
summary, the research ndings reviewed above indicate that trust in
COVID-19-related information from ocial media could either
positively, or negatively aect public’s wellbeing and that perceived
safety might play a mediating role. Hence, weproposed that trust in
ocial media was signicantly related to public’s wellbeing both directly
and indirectly through perceived safety (Hypotheses 4 and 5), but
wele the direction of the relationships (i.e., positive or negative) open.
H4: Trust in COVID-19-related information from ocial media was
signicantly (either positively or negatively) associated with positive
and depressive emotional responses toward COVID-19 respectively.
H5: Perceived safety mediates the relationship between trust in
ocial media with positive and negative responses toward
COVID-19 respectively.
The present study
e present study aimed to investigate how trust in the information
about COVID-19 from ocial media and social media aect public’s
wellbeing (i.e., positive response and depressive response) through
perceived safety, and how the dissemination of information impact
public trust in ocial media both at the early stage of COVID-19
outbreak and 2 years later in China. To our best knowledge, this is the
rst study to examine the impacts of trust in media sources on public’s
wellbeing toward COVID-19 over time. e insights developed through
this study will help policy makers and health intervention initiatives
develop targeted strategies to address the mental health challenges
presented by the COVID-19 pandemic and protect public’s wellbeing.
Figure1 presents a path model which summarizes the hypotheses
proposed above. In this model, wepropose that trust in COVID-19
information received from social media was negatively associated with
positive emotional response and positively associated with depressive
emotional response toward COVID-19 both directly and indirectly
through decreased perceived safety (H1-H2); that perceived
transparency and rapid dissemination of COVID-19-related
information are positively related to trust in ocial media (H3). In
turn, trust in ocial media was either positively or negatively
associated with positive and depressive response toward COVID-19
both directly and indirectly through perceived safety (H4, H5).
ough the scientic understanding of COVID-19 has been
advanced over 2 years into the pandemic, the “infodemic” wasn’t over.
Rumors and misinformation about the virus and vaccine were still
widespread across social media (8). In addition, the mental health
symptoms were still quite prevalent among public in the “new normal”
era (59). erefore, it’s important to examine the mechanism of trust
in media sources aect public’s wellbeing over time. e path
framework weproposed allows the examination of how the key factors
aect public’s wellbeing both at the early stage of COVID-19 outbreak
and post COVID-19 era and also allows to make comparisons of the
changes in eects. e developed insights on what has changed over
time will inform policy makers to adjust the risk communication
strategies accordingly.
2. Materials and methods
2.1. Procedure and participants
National online surveys in China were conducted at the early
stage of COVID-19 outbreak and 2 years later. Time 1 survey was
FIGURE1
An integrative model to predict emotional responses toward the COVID-19.

Zhou et al. 10.3389/fpubh.2023.1142230
Frontiers in Public Health 04 frontiersin.org
carried out between 24-Jan to 10-Feb, 2020, which was right aer
China’s ocial announcement of COVID-19 outbreak (on January 20,
2020) and deployed lockdown measures (on January 23, 2020). Time
2 survey was conducted between 21-Apr to 4-May, 2022, when Delta
and Omicron variants were widely spread around the world and
COVID-zero policy was still in place in China (60). e study was
conducted in compliance with the ethical standards specied in the
Ethical Principles of Psychologists and Code of Conduct by the
American Psychological Association (61) and in 1964 Helsinki
declaration and its later amendments (62). Two private research
survey companies (Intell-vision for Time 1, ePanel for Time 2) were
engaged to recruit participants and conduct data collection through
convenance sampling. e survey link was sent to users of the online
survey platforms of the two companies. Aer presenting a brief
description of the study, participants were informed that no personal
identiable information would be collected and that their survey
results would remain condential. Participants were further informed
that their participation was voluntary and that they could withdraw
from the survey at any time without penalty. Participants were asked
to click ‘I agree’ button if they consent to participate in the survey.
Participants who completed the survey were paid a small fee for their
participation. e collected data was completely anonymous, and the
research team was the only party has access to the data.
Table1 presents participants’ demographic information for both
Time 1 and Time 2.
2.2. Measures
2.2.1. Trust in ocial media
At the early stage of COVID-19 outbreak, the ocial news
reached the public largely through television news and it was also
available online in China. e TV news report is in the format of
news from central government rst and followed by news from local
government. Hence, at Time 1, trust in ocial media was measured
by asking participants to indicate how trustworthy the information
on the Coronavirus outbreak from central government-owned media
and local government-owned media, respectively, on a 4-point scale
(1 = not trustworthy at all, 4 = very trustworthy; α = 0.75). While
2 years later, community social workers also became important
information sources. ey conveyed ocial information on
COVID-19 to the public and implemented preventive and control
measures at community level. erefore, at Time 2, trust in ocial
media was measured by asking participants to indicate how
trustworthy the information on COVID-19 from central government-
owned media, local government-owned media, and community
social workers, respectively, on a 5-point scale (1 = not trustworthy at
all, 5 = very trustworthy; α = 0.75). To compare the change between
Time 1 and Time 2, the score of trust in ocial media at Time 1 was
transformed to a 5-point scale by using the following formula (63, 64):
XX
143
13
=
()
−
()
∗
//
Here:
X1: Transformed score of trust in ocial media (on a 5-point scale).
X: the original score of trust in ocial media (on a 4-point scale).
2.2.2. Trust in social media
In the beginning of COVID-19 outbreak, Weibo and WeChat were
the most popular social media platforms in China for the spread of
information about COVID-19. Besides, acquaintances were also
important information sources during the pandemic. Hence, at Time
1, trust in social media was measured by asking participants to indicate
how trustworthy the information on the Coronavirus outbreak from
Weibo inuencers, WeChat inuencers, and acquaintances,
respectively, on a 4-point scale (1 = not trustworthy at all, 4 = very
trustworthy; α = 0.77). As time passed by, the general netizens became
more and more important in information transmission. erefore, at
Time 2, trust in social media was measured by asking participants to
indicate how trustworthy the information on COVID-19 from internet
inuencers, general netizens, and acquaintances, respectively, on a
5-point scale (1 = not trustworthy at all, 5 = very trustworthy; α = 0.68).
e Cronbach’s alpha for trust in social media at Time 2 is a bit lower
than the widely considered desirable value of 0.70 (65, 66). However, a
low number of items could lead to a low value of Cronbach’s alpha (65).
Since there were only 3 items in this scale, an alpha value of 0.68 is
acceptable (67, 68). To examine the dierence between Time 1 and
Time 2, the score of trust in social media at Time 1 was also transformed
to a 5-point scale by using the formula described above (63, 64).
2.2.3. Rapid dissemination, transparency, and
perceived safety
Rapid dissemination was measured with: “So far, do youthink the
dissemination of information about Coronavirus is rapid?” (1 = very
delayed, 4 = very rapid). Transparency was measured with: “So far,
how transparent do youthink the information on the Coronavirus
outbreak is?” (1 = very low, 4 = very high). Perceived safety was
measured with: “inking about Coronavirus, how safe do youfeel
from being infected?” (1 = not safe at all, 4 = very safe).
2.2.4. Emotional responses
e measurement of emotional responses toward COVID-19
outbreak was adapted from the Florida Shock Anxiety Scale (69, 70).
TABLE1 The sample characteristics.
Variables Values
Time 1
(N = 22,702)
Time 2
(N = 2,901)
Age (years) 28.41 (SD = 9.90/
Range = 18–70)
31.77 (SD = 8.05/
Range = 18–69)
Gender
Male 10,866 (47.9%) 1,274 (43.9%)
Female 11,836 (52.1%) 1,627 (56.1%)
Education
Junior high school and
below (Year 9 or below) 796 (3.5%) 16 (0.6%)
Senior high school
(Year 12) 3,287 (14.5%) 137 (4.7%)
College certicate 3,514 (15.5%) 416 (14.3%)
Bachelor’s degree 10,952 (48.2%) 2,115 (72.9%)
Postgraduate 4,153 (18.3%) 217 (7.5%)

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e Florida Shock Anxiety Scale (FSAS) was developed to measure
patients’ psychological distress caused by the threat and fear of
potential implantable cardioverter debrillators (ICD) shock. e
COVID-19 pandemic has instilled people with a sense of fear of being
infected with the virus. e potential infection may happen but is not
certain, which makes people feel worried, scared, and angry. is
psychological distress is very similar to that elicited from the
anticipation of experiencing ICD shock. Hence, weadapted this scale
to measure the emotional responses toward COVID-19. Participants
were asked to rate their feelings toward COVID-19 outbreak using a
5-point scale (1 = not at all, 5 = very much) on the adjectives describing
positive response (optimistic) and depressive response (worried,
scared, sad, and angry; α = 0.80 at Time 1, α = 0.81 at Time 2).
2.3. Data analysis
SPSS version 22.0 with AMOS version 24.0 was used for the data
analysis. Descriptive statistical analysis, independent samples t-test, and
Pearson correlations were conducted rst. To examine the hypothesized
model (Figure1), A two-stage structural equation modeling approach
was conducted (71–77). e analyses for the model at both Time 1 and
Time 2 utilized a covariance matrix as input and used maximum
likelihood estimation. e goodness of t of the model was assessed
using the comparative t index (CFI), the Non-Normed Fit Index
(NNFI), Goodness-of-t statistic (GFI), and root mean square error of
approximation (RMSEA). A satisfactory t is suggested by CFI > 0.90,
NNFI > 0.90, GFI > 0.90, and Standardized RMSEA < 0.08 (72).
3. Results
3.1. Changes in measured variables over
time
Table2 presents the means and standard deviations of measured
variables at both survey times and independent samples t-test results
between the two time points. On average, participants displayed sound
trust in ocial media both at Time 1 (M = 3.94, SD = 0.84) and Time 2
(M = 4.17, SD = 0.67), which were signicantly higher than trust in social
media at both times (Time 1, M = 3.07, SD = 0.86, Time 2, M = 3.04,
SD = 0.67); t (22701) = 131.58, p < 0.001 and t (2900) = 72.87, p < 0.001,
respectively. Moreover, trust in ocial media at Time 2 was signicantly
higher than Time 1 [t (4161.46) = −17.18, p < 0.001], while trust in social
media at Time 2 was signicantly lower than Time 1 [t (4225.96) = 2.50,
p < 0.05]. e results indicated that trust in ocial media largely
increased over time, while trust in social media decreased over time.
e dissemination of information about the Coronavirus was
regarded on average less rapid (M = 2.75, SD = 0.87) and transparent
(M = 2.75, SD = 0.78) at Time 1. However, both measures were
signicantly improved at Time 2 (rapid dissemination: M = 3.19,
SD = 0.64, transparency: M = 3.08, SD = 0.71); Rapid dissemination: t
(4394.35) = −33.40, p < 0.001; Transparency: t (3866.79) = −23.31,
p < 0.001. Perceived safety from being infected with the Coronavirus
also enhanced from Time 1(M = 2.80, SD = 0.68) to Time 2 (M = 2.89,
SD = 0.65), t (3760.10) = −7.22, p < 0.001. At last, positive emotional
response toward COVID-19 increased over time (Time 1, M = 3.07,
SD = 1.27, Time 2, M = 3.33, SD = 0.94); t (4405.12) = −13.41, p < 0.001,
while depressive response decreased over time (Time 1, M = 3.22,
SD = 1.00, Time 2, M = 3.09, SD = 0.87); t (3951.96) = 7.41, p < 0.001.
Table 3 presents Pearson correlations between the measured
variables at both survey times. Positive response was positively related
to trust in ocial media and social media as well as rapid
dissemination, transparency, and perceived safety both at Time 1 and
Time 2, while depressive response was negatively associated with these
variables (except for trust in social media at Time 1, which was not
signicantly correlated to depressive response). In addition, trust in
ocial media and social media, rapid dissemination, transparency, and
perceived safety were positively correlated to each other at both survey
times (except for trust in social media and perceived safety at Time 2,
which was not signicantly correlated). Finally, positive response and
depressive response was negatively related at both survey times.
3.2. The relationship among information
dissemination, trust in media sources,
perceived safety, and emotional responses
over time
A two-stage structural equation modeling approach was
conducted (71–77) to examine the hypothesized model. In this
approach, the measurement model, which species the relationships
TABLE2 Descriptive statistics and independent samples t-test results for measured variables.
M (SD) tdf Cohen’ d
Time 1 (N = 22,702) Time 2 (N = 2,901)
Trust in ocial media 3.94 (0.84) 4.17 (0.67) −17.18*** 4161.46 −0.28
Trust in social media 3.07 (0.86) 3.04 (0.67) 2.50*4225.96 0.04
Rapid dissemination 2.75 (0.87) 3.19 (0.64) −33.40*** 4394.35 −0.52
Transparency 2.75 (0.78) 3.08 (0.71) −23.31*** 3866.79 −0.43
Perceived safety 2.80 (0.68) 2.89 (0.65) −7.22*** 3760.10 −0.13
Positive response 3.07 (1.27) 3.33 (0.94) −13.41*** 4405.12 −0.21
Depressive response 3.22 (1.00) 3.09 (0.87) 7.41*** 3951.96 0.13
***p < 0.001, *p < 0.05. Trust in ocial media and trust in social media were measured on a 5-point scale (1 = not trustworthy at all, 5 = very trustworthy). Rapid dissemination was measured
on a 4-point scale (1 = very delayed, 4 = very rapid). Transparency was measured on a 4-point scale (1 = ver y low, 4 = very high). Perceived safety was measured on a 4-point scale (1 = not safe at
all, 4 = ver y safe). Positive response and depressive response were measured on a 5-point scale (1 = not at all, 5 = very much).

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between the latent constructs and the observed measures, was tested
rst via conrmatory factor analysis (CFA); followed by the
structural model, which species the relationships among
independent, dependent, and mediating variables. In addition, the
bias-corrected bootstrap method was carried out to test the indirect
eects. 5,000 bootstrapped samples were generated to approximate
the condence interval (CI) of the indirect eects both at Time 1 and
Time 2. A 95% CI without zero indicates statistical signicance.
Furthermore, following the practice of previous studies (78, 79), the
structural model was tested for robustness by changing the
sample range.
3.2.1. Confirmatory factor analysis (CFA) for the
measurement model
Conrmatory factor analysis (CFA) was conducted to examine the
measurement model both at Time 1 and Time 2. e measurement
model was supported by the model t indexes at both survey times:
Time 1, CFI = 0.97, NNFI = 0.96, GFI = 0.98, and RMSEA = 0.06; Time
2, CFI = 0.93, NNFI = 0.90, GFI = 0.96, and RMSEA = 0.08.
Furthermore, the convergent and discriminant validity of the
measurement model were assessed at both times. e convergent
validity was evaluated by using standardized factor loadings,
composite reliability (CR) and the average variance extracted (AVE)
(see Table 4). All items loaded signicantly on their respective
constructs, with the standardized factor loadings ranging from 0.50 to
0.85, reaching the criterion of 0.50 or above (74). e CR values
ranged from 0.68 to 0.81, meeting an acceptable criterion of 0.60 (74).
e AVE values ranged from 0.42 to 0.68, reaching the criterion of
0.36 or above (77). ese results provided evidence of satisfactory
convergent validity. Discriminant validity was assessed by comparing
AVE with the squared correlation between constructs. e squared
correlations between constructs at both times ranged from 0.00 to
0.20, which were all much lower than AVE values, indicating that the
measurement model has satisfactory discriminant validity (73–75).
ese results suggested that the measurement model is of
sucient quality to examine the structural model.
3.2.2. Pathway analysis for the structural model
Our hypothesized model (Figure1) specied rapid dissemination
and transparency of information as exogenous predictors of trust in
ocial media, both trust in ocial media and social media as
exogenous predictors of perceived safety. Perceived safety, in turn, was
identied as a predictor of positive response and depressive response.
Moreover, trust in ocial media and trust in social media also served
as exogenous predictors of positive response and depressive response.
In this model, trust in ocial media, trust in social media, and
depressive response were latent variables presented using ellipses,
while rapid dissemination, transparency, positive response (optimistic)
and perceived safety were observed variables presented
using rectangles.
e model t indices suggest that the model provided good t for
the data at both times: Time 1, CFI = 0.94, NNFI = 0.92, GFI = 0.96,
and RMSEA = 0.07; Time 2, CFI = 0.92, NNFI = 0.90, GFI = 0.95, and
RMSEA = 0.07.
Figure2 presents the standardized parameter estimates for the
model at both Time 1 (T1) and Time 2 (T2). Table 5 presents the
direct, indirect, and total eects of trust in media sources on public’s
wellbeing at both Time 1 (T1) and Time 2 (T2).
First, trust in social media was negatively related to positive
response at Time 1 (β = −0.16, p < 0.001) and positively associated with
depressive response both at Time 1(β = 0.30, p < 0.001) and Time 2
(β = 0.08, p < 0.001), such that the more people trusted the information
about the Coronavirus received in social media, the less they felt
optimistic and the more they felt depressive toward the pandemic,
especially in the beginning of COVID-19 outbreak. Since trust in social
media was no longer signicantly related to positive response at Time 2
(β = 0.01, p = 0.684), Hypothesis 1 was fully supported at Time 1 and was
partially supported at Time 2. Moreover, Trust in social media was
negatively associated with perceived safety at Time 1 (β = −0.10,
p < 0.001), but not signicantly associated with perceived safety at Time
2 (β = −0.04, p = 0.096). In turn, perceived safety was positively related
to positive response (Time 1, β = 0.11, p < 0.001; Time 2, β = 0.16,
p < 0.001) and negatively linked to depressive response (Time 1,
TABLE3 Pearson correlations between the measured variables at Time 1 and Time 2.
Variables 1 2 3 4 5 6
Time 1 Time 2 Time 1 Time 2 Time 1 Time 2 Time 1 Time 2 Time 1 Time 2 Time 1 Time 2
1. Trust in ocial
media 1.00 1.00
2. Trust in social
media 0.33*** 0.22*** 1.00 1.00
3. Rapid
dissemination 0.46*** 0.48*** 0.26*** 0.12*** 1.00 1.00
4. Transparency 0.49*** 0.52*** 0.28*** 0.16*** 0.69*** 0.68*** 1.00 1.00
5. Perceived
safety 0.31*** 0.14*** 0.22*** 0.03 0.35*** 0.14*** 0.37*** 0.16*** 1.00 1.00
6. Positive
response 0.28*** 0.26*** 0.18*** 0.12*** 0.36*** 0.22*** 0.36*** 0.27*** 0.31*** 0.23*** 1.00 1.00
7. Depressive
response
−0.18*** −0.19*** 0.01 −0.04* −0.24*** −0.21*** −0.23*** −0.24*** −0.28*** −0.25*** −0.20*** −0.38***
***p < 0.001, *p < 0.05. Trust in ocial media and trust in social media were measured on a 5-point scale (1 = not trustworthy at all, 5 = very trustworthy). Rapid dissemination was measured
on a 4-point scale (1 = very delayed, 4 = very rapid). Transparency was measured on a 4-point scale (1 = ver y low, 4 = very high). Perceived safety was measured on a 4-point scale (1 = not safe at
all, 4 = ver y safe). Positive response and depressive response were measured on a 5-point scale (1 = not at all, 5 = very much).

Zhou et al. 10.3389/fpubh.2023.1142230
Frontiers in Public Health 07 frontiersin.org
β = −0.20, p < 0.001; Time 2, β = −0.21, p < 0.001) at both survey times,
suggesting that the safer people felt, the more they were optimistic and
the less they were depressed. ese results indicated that perceived
safety served as a mediator between trust in social media and emotional
responses toward COVID-19 at Time 1 but not at Time 2. us,
Hypothesis 2 was only supported at Time 1.
Second, trust in ocial media was strongly associated with rapid
dissemination (Time 1, β = 0.35, p < 0.001; Time 2, β = 0.29, p < 0.001)
and transparency (Time 1, β = 0.44, p < 0.001; Time 2, β = 0.46,
p < 0.001) over time, such that the more people believed information
dissemination as rapid and transparent, the more they trusted ocial
media both at the early stage of COVID-19 outbreak and 2 years later.
us, Hypothesis 3 was supported at both survey times.
ird, trust in ocial media was positively related to positive
response (Time 1, β = 0.46, p < 0.001; Time 2, β = 0.34, p < 0.001) and
was negatively associated with depressive response (Time 1, β = −0.34,
p < 0.001; Time 2, β = −0.32, p < 0.001) over time, such that the more
people trusted the information about the Coronavirus given by ocial
media, the more they responded optimistically and the less they felt
depressively toward the pandemic. Hence, the results provided
support for a positive relationship between trust in ocial media and
public’s wellbeing of Hypothesis 4 at both survey times. Furthermore,
trust in ocial media was positively associated with perceived safety
at both times (Time 1, β = 0.50, p < 0.001; Time 2, β = 0.20, p < 0.001),
such that the more people trusted the information about the
Coronavirus given by ocial media, the more they felt safe from being
TABLE4 The standardized factor loadings, composite reliability (CR), and average variance extracted (AVE) of each construct in measurement model at
Time 1 and Time 2.
Construct Time 1 Time 2
Item Standardized
factor loading
CR AVE Item Standardized
factor loading
CR AVE
Trust in ocial
media
Central
government-
owned media
0.60
0.80 0.68
Central
government-
owned media
0.74
0.76 0.52Local government-
owned media 1.00 Local government-
owned media 0.84
Community social
workers 0.56
Trust in social
media
WeChat
inuencers 0.82
0.79 0.56
Internet
inuencers 0.73
0.68 0.42
Weibo inuencers 0.85 General netizens 0.70
Acquaintances 0.54 Acquaintances 0.50
Depressive
response
Worried 0.62
0.80 0.51
Worried 0.66
0.81 0.52
Scared 0.77 Scared 0.75
Sad 0.79 Sad 0.79
Angry 0.66 Angry 0.68
CR: Composite reliability, AVE: Average variance extracted.
FIGURE2
The relationship among information dissemination, trust in media sources, perceived safety, and emotional responses over time.

Zhou et al. 10.3389/fpubh.2023.1142230
Frontiers in Public Health 08 frontiersin.org
infected. In turn, the safer people felt, the more they felt optimistic and
the less they felt depressed. at is, perceived safety mediated the
relationship between trust in ocial media and emotional responses
toward COVID-19 both at Time 1 and Time 2. us, Hypothesis 5 was
supported by a positive mediating eect of perceived safety between
trust in ocial media and public’s wellbeing at both survey times.
e robustness of the structural model was tested by changing the
sample range (78, 79). To examine if the structural model only held
due to high trust in media sources, weremoved a portion of the
sample with high trust scores (> 4 out of a possible 5) either in ocial
media or social media. e structural model still held aer changing
the sample range. And all signicant coecients in the structural
model remain signicant in robustness check. ese results suggest
that our ndings are relatively robust.
4. Discussion
e present research applied a longitudinal approach to examine
how trust in media sources aect public’s wellbeing through perceived
safety and how the dissemination of information contributes to
increased public trust in ocial media during the course of
COVID-19 pandemic.
e results of the present study suggest that the public had more
trust in the information about COVID-19 from the ocial media
outlets than from the social media both at the early stage of the
pandemic outbreak and 2 years later. e comparatively higher trust
in ocial media is likely due to that the ocial media represents the
voice of the government and is regarded as highly reliable during a
pandemic (80, 81). In addition, trust in ocial media was signicantly
increased over a two-year period, which is opposite to research
ndings from Europe and the USA showing trust in ocial media
decreased both in short-term (82) and in long-term (83, 84) during
the COVID-19 pandemic. In contrast, trust in social media was
slightly decreased two years aer COVID-19 outbreak.
Public perceptions of rapid dissemination and transparency
regarding information about the Coronavirus also increased over
time, which is likely due to the open and transparent risk
communication implemented by governments. During COVID-19
pandemic, the Chinese government disclosed real-time data in detail
on conrmed, suspected, and cured cases, as well as deaths across the
country. It also issued national action plans and released authoritative
interpretations of the coronavirus to mitigate public panic and doubts
(85). Moreover, public’s wellbeing was signicantly improved over the
2 years period, which is in line with research ndings from UK (86)
and the USA (59).
While the social media were ooded with information and
sensational news about COVID-19, public’s trust in them was low.
However, trust in social media played a dominant role in contributing
to increased depressive symptoms in the early stage of COVID
pandemic. e negative impact of trust in social media was largely
reduced over time. In contrast, trust in the information from ocial
media was higher, and it played an inuential role in contributing to
enhanced positive response and decreased depressive symptoms both
at the beginning of the pandemic and over 2 years later. While existing
literature points to both positive and negative directions regarding
how trust in ocial media would aect mental wellbeing during
COVID-19 pandemic (51–58), the present study provides evidence
for a positive eect of trust in COVID-19-related information from
ocial media on public’s wellbeing in Chinese context over time. e
ndings suggest that enhancing public trust in information from
ocial media will bean eective approach to ght against the so called
COVID-19 infodemic and protect public’s wellbeing. is has
signicant implications for public health measures to combat the
pandemic of social media panic. To eectively minimize the negative
impact of social media on public mental health, health authorities
TABLE5 The direct, indirect, and total eects of trust in media sources on public’s wellbeing at Time 1 and Time 2.
Paths Time 1 Time 2
Standardized
eect
95% CI Standardized
eect
95% CI
Direct eects
Trust in ocial media → positive response 0.46*** (0.436, 0.479) 0.34*** (0.289, 0.396)
Trust in ocial media → depressive response −0.34*** (−0.360, −0.312) −0.32*** (−0.373, −0.255)
Trust in social media → positive response −0.16*** (−0.181, −0.133) 0.01 (−0.046, 0.065)
Trust in social media → depressive response 0.30*** (0.281, 0.328) 0.08** (0.020, 0.150)
Indirect eects
Trust in ocial media → perceived safety → positive response 0.06*** (0.048, 0.063) 0.03*** (0.023, 0.044)
Trust in ocial media → perceived safety → depressive response −0.10*** (−0.109, −0.092) −0.04*** (−0.057, −0.032)
Trust in social media → perceived safety → positive response −0.01*** (−0.015, −0.008) −0.01 (−0.015, 0.002)
Trust in social media → perceived safety → depressive response 0.02*** (0.016, 0.026) 0.01 (−0.003, 0.019)
Total eects
Trust in ocial media → positive response 0.51*** (0.494, 0.532) 0.38*** (0.321, 0.427)
Trust in ocial media → depressive response −0.44*** (−0.458, −0.415) −0.36*** (−0.414, −0.298)
Trust in social media → positive response −0.17*** (−0.194, −0.143) 0.00 (−0.054, 0.061)
Trust in social media → depressive response 0.33*** (0.300, 0.350) 0.09** (0.026, 0.160)
***p < 0.001, **p < 0.01.

Zhou et al. 10.3389/fpubh.2023.1142230
Frontiers in Public Health 09 frontiersin.org
need to rapidly detect and respond to misinformation and rumors in
social media.
e present research demonstrated that trust in ocial media was
positively correlated with rapid dissemination and transparency of the
information about COVID-19 over time. Hence, fostering and
maintaining public’s trust requires rapid dissemination and
transparency of information. e trust-building function of
transparency revealed in the present study is in line with literature on
the general relationship between transparency and public trust (43,
48, 87, 88). Research on infectious disease found that public trust in
government and public health authorities as information source
inuences public perceived risk and their responses to the threat (47,
88–91). e present study further shows that rapid dissemination of
information and transparency works hand in hand. ese ndings
suggest that government and health authorities need to rapidly
disseminate information and update the outbreak through various
platforms including their social media accounts to accommodate all
segments of the population. e information needs to betransparent,
even though communicating uncertainty and a lack of knowledge in
the case of the novel COVID-19 can beunsettling. Otherwise, the
absence of ocial information creates a rich breeding ground for
misinformation and rumors in social media, which can further
exacerbate the fear caused by the objectively life-threatening nature of
the coronavirus. A trusted ocial media based on transparency and
rapid dissemination of COVID-19-related information can keep the
public informed and enable them to develop a sense of agency through
knowing how to manage the risks.
While the present study has shed light on the negative impacts of
trust in social media sources on wellbeing, future research needs to
unpack the complexity of social media. e information in social media
is diverse and sometimes contradicting. In addition, the information
may come from a wide range of sources including people sharing
information acquired from ocial sources (48). us, how trust in
social media aect public’s wellbeing may depend on the contents and
sources. For example, a literature review has shown that viewing
stressful content about COVID-19 outbreak on social media was linked
to poor psychological outcomes, while viewing motivational and heroic
speech, knowledge of COVID-19, and entertaining contents was related
to positive psychological wellbeing (45). To unpack the complexity of
trust in social media, future research needs to tease apart the
information source and contents on social media. e insights will help
policy makers and health authorities develop targeted strategy to
harness the benets of social media and mitigate the negative impacts.
Moreover, to fully utilize the protective role of trust in ocial media, an
in-depth examination of what key aspects of pandemic related
information important for the public is needed. Such insights would
inform a more targeted strategy for rapid dissemination. Noticeably,
though trust in ocial media can protect public’s wellbeing against
COVID-19 infodemic, this does not mean all the information given by
ocial media is the absolute truth. Scientic understanding of
COVID-19 is evolving constantly, such that what qualies as
misinformation might besubjective to new scientic discoveries (6). In
addition, fear-based communication strategies may raise public
adherence to health recommendations for COVID-19, but such
strategies might negatively aect public’s wellbeing (51, 53, 55, 92–94).
Future research can unpack the contents and approaches adopted by
ocial media to identify eective communication strategies in
conveying information eciently while protecting public’s wellbeing. At
last, although the current study took a longitudinal approach (95), it’s
not a follow-up study with the same participants. Future research needs
to follow up the same participant sample to further verify the impact of
trust in media sources on public’s wellbeing over time.
In summary, the present study has empirically and longitudinally
demonstrated that the COVID-19 infodemic can have serious
consequence for public’s wellbeing. Especially, trust in the information
about COVID-19in social media was associated with stronger depressive
response at the beginning of pandemic. However, trust in ocial media
can mitigate this negative impact. More importantly, the rapid
dissemination and transparency of information regarding the virus can
enhance public trust in the information from ocial media outlets. e
ndings highlight that, to protect public’s wellbeing against COVID-19
infodemic, government and health authorities need to rapidly disseminate
information and betransparent even though communicating uncertainty
and unknowns can be unsettling. Otherwise, the absence of ocial
information creates a rich breeding ground for misinformation and
rumors in social media, which has huge consequence for public’s
wellbeing, especially at the early stage of the pandemic.
Data availability statement
e raw data supporting the conclusions of this article will
bemade available by the authors, without undue reservation.
Ethics statement
e studies involving human participants were reviewed and
approved by e Academic Committee of Institute of Sociology,
Chinese Academy of Social Sciences (CASS). Written informed
consent for participation was not required for this study in accordance
with the national legislation and the institutional requirements.
Author contributions
JW, YiZ, and AZ conceived and designed the study. JW, XL, and
XT contributed to data collection. YiZ analyzed the data. YiZ, AZ,
RM, XT, and XL wrote the rst dra of the manuscript. YiZ, AZ, and
YaZ revised the manuscript. All authors contributed to the article and
approved the submitted version.
Funding
e study was funded by Key Projects of Philosophy and Social
Sciences Research, Ministry of Education of the People’s Republic of
China (Award number: 21JZD038) and China Scholarship Council
(CSC Award Number: 202004920045).
Conflict of interest
e authors declare that the research was conducted in the
absence of any commercial or nancial relationships that could
beconstrued as a potential conict of interest.

Zhou et al. 10.3389/fpubh.2023.1142230
Frontiers in Public Health 10 frontiersin.org
Publisher’s note
All claims expressed in this article are solely those of the
authors and do not necessarily represent those of their aliated
organizations, or those of the publisher, the editors and the
reviewers. Any product that may be evaluated in this article, or
claim that may be made by its manufacturer, is not guaranteed or
endorsed by the publisher.
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