An Empirical Study of the Toxic Capsule Crisis in China:
Risk Perceptions and Behavioral Responses
Tianjun Feng
tfeng@fudan.edu.cn
School of Management
Fudan University, Shanghai, P.R. China 200433
L. Robin Keller
LRKeller@uci.edu
The Paul Merage School of Business
University of California, Irvine
Irvine, CA, U.S.A. 92697-3125
Ping Wu
12110690016@fudan.edu.cn
School of Management
Fudan University, Shanghai, P.R. China 200433
Yifan Xu
yfxu@fudan.edu.cn
School of Management
Fudan University, Shanghai, P.R. China 200433
6-22-2013
Forthcoming, Risk Analysis
* Please address correspondence to L. Robin Keller (LRKeller@uci.edu).
0
ABSTRACT
The outbreak of the toxic capsule crisis during April 2012 aroused widespread public
concern about the risk of chromium-contaminated capsules and drug safety in China.
In this paper, we develop a conceptual model to investigate risk perceptions of the
pharmaceutical drug capsules and behavioral responses to the toxic capsule crisis and
the relationship between associated factors and these two variables.
An online
survey was conducted to test the model, including questions on the measures of
perceived efficacy of the countermeasures, trust in the State FDA (Food and Drug
Administration), trust in the pharmaceutical companies, trust in the pharmaceutical
capsule producers, risk perception, concern, need for information, information
seeking, and risk avoidance.
In general, participants reported higher levels of risk
perception, concern, and risk avoidance, and lower levels of trust in the three different
stakeholders. The results from the structural equation modeling procedure suggest
that perceived efficacy of the countermeasures is a predictor of each of the three trust
variables; however, only trust in the State FDA has a dampening impact on risk
perception.
Both risk perception and information seeking are significant
determinants of risk avoidance. Risk perception is also positively related to concern.
Information seeking is positively related to both concern and need for information.
The theoretical and policy implications are also discussed.
KEY WORDS: Toxic capsules; risk perception; behavioral response; pharmaceutical
products; trust; structural equation modeling
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Risk Perceptions and Behavioral Responses
1. INTRODUCTION
In recent years, China has suffered from a number of food safety scandals, such as
contaminated milk powder, swill-cooked dirty oil, tainted steamed buns, etc. Those
crises have made the Chinese people more and more concerned about food safety
issues and strongly weakened their trust in the food industry of China. Surprisingly,
in 2012, the most influential safety-related crisis in China was not related to the food
industry, but broke out in the drug industry.
In April 2012, the toxic drug capsule
crisis hit the headlines in China when the state broadcaster CCTV (China Central
Television) reported that several capsule manufacturers in the Xinchang County of
Zhejiang Province made and sold capsules with excessive levels of chromium after
using industrial gelatin made from discarded leather.(1)
Further investigations
revealed that capsules made from industrial gelatin were in 13 commonly used drugs
in the Chinese market, which were manufactured by nine domestic pharmaceutical
companies, including the well-known Xiuzheng Pharmaceutical Group in Jilin
province.(2)
Those contaminated capsules contained more than 90 times the
allowable upper limit of chromium, imposing a health hazard since chromium can be
toxic and carcinogenic if ingested in excessive amounts.(3) Consequently, China’s
State Food and Drug Administration (FDA) suspended sales of the 13 medicines with
excessive levels of chromium, and the police arrested 22 people for making toxic drug
capsules.(4)
On August 4th, the State FDA announced that 76 local officials,
employees of drug supervision agencies in five provinces and the municipality of
Chongqing, had been punished because they had failed to prevent and stop the
production of toxic drug capsules.(3)
The toxic capsule scandal led to an immediate panic among the Chinese public.
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Risk Perceptions and Behavioral Responses
They were greatly worried about drug safety. Some expressed anger, such as
“How can you make capsules from the broken shoes I threw away?”(3)
Some of them strongly complained about the crisis,
“This is ridiculous.
people who are sick.
Medicines are supposed to be safe and cure
Those medicines are indeed toxic and may
make patients even worse. What can we trust in this world?”(3)
More people raised serious concerns about the responsibilities of the stakeholders
involved in the scandal, e.g.,
“Can we still believe in those pharmaceutical companies?” “Can we
still trust the regulation of the Food and Drug Administration, and
other associated agencies?” etc.(3)
Considering the reactions of the public, it is important to understand which factors
have an influence upon risk perceptions and behavioral responses of this particular
risk.
There is abundant related research that studies risk perception and behavioral
responses in various contexts, such as food safety,(5-10) product safety ,(11-13) pandemic
or malignant diseases,(14-20) and natural hazards.(21-24) Drug safety has also been
widely documented in the literature.(25-27) This stream of literature mainly focuses
on the risk of drug use, including medical errors or misuse,(26,28,29) adverse events or
experiences,(30,31) and adverse drug reactions.(32-34)
However, to the best of our
knowledge, no research has examined risk perception of toxic drug capsules.
In this
paper, we are interested in investigating how people perceive the risk associated with
toxic drug capsules and what the determinants are of their risk perceptions and
3
Risk Perceptions and Behavioral Responses
responses toward the crisis.
A number of papers have employed structural equation models to examine factors
affecting people’s risk perceptions and actions for different risks.(6,14,35-37)
For
example, by using the structural equation modeling method, Siegrist(36) explores the
determinants of risk perceptions and acceptance of gene technology.
Tanaka(35)
extends Siegrist’s(36) framework to identify psychological factors affecting acceptance
of gene-recombination technology using a structural equation model. Kuttschreuter(6)
develops a structural equation model to explore the psychological determinants of the
responses to food risk messages.
Using structural equation modeling, Allum(37)
studies the relationship between trust and risk perceptions of genetically modified
food.
Prati et al.(14) use a structural equation model to investigate cognitive,
social-contextual, and affective factors influencing risk perceptions and responses to
the pandemic influenza H1N1 (swine flu) in Italy.
Following this stream of
literature, this paper develops a hypothesized framework to determine the factors that
have an impact on risk perceptions and responses to the toxic capsule crisis, based on
a structural equation model.
The paper is organized as follows.
We first propose a conceptual model of risk
perceptions of the toxic capsule crisis and behavioral responses to the crisis in Section
2. Next, in Section 3, we present our methodology.
In Section 4, we report the
main results. Finally, we provide a detailed discussion about the results as well as
the limitations of this study and future research directions.
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Risk Perceptions and Behavioral Responses
2. HYPOTHESIZED MODEL
Many studies have explored the relationship between trust and risk
perception.(36,38-44) Trust has been identified as one of the key predictors of people’s
risk perceptions. For example, Freudenburg(45) argues that people who trust the
abilities to safely dispose of nuclear waste in their country tend to have lower levels
of perceived risk of nuclear waste.
Siegrist(46) suggests that trust in institutions using
gene technology is negatively associated with the perceived risk of this technology.
Through an empirical investigation of the relationship between trust and risk
perception in four European countries, Viklund(41) shows that trust is a significant
determinant of perceived risk within countries.
Kuttschreuter(6) provides empirical
evidence that higher levels of trust in the safety of a product or an organization lead to
lower levels of perceived risk.
Furthermore, it has been documented in the literature that people have different
degrees of trust in different parties, i.e., they trust consumer organizations, quality
media and medical doctors the most, the food industry second, and government
sources the least.(39)
In the toxic capsule crisis, three major stakeholders were
closely involved: the capsule producers, the pharmaceutical companies, and the State
FDA of China.
It is plausible to suspect that Chinese people have different levels of
trust in those three stakeholders. As a result, in this study, we postulate that trust in
the State FDA, trust in the pharmaceutical companies, and trust in the pharmaceutical
capsule producers have a negative influence on risk perception.
Perceived efficacy of countermeasures has been found to be an important factor
affecting people’s trust in different organizations when they are faced with certain
risks.(47-49)
Through a laboratory study, Schweitzer et al.(50) find that a set of
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Risk Perceptions and Behavioral Responses
trustworthy actions can effectively restore people’s trust.
Lewicki and Wiethoff
argue that it is relatively easy to take some countermeasures to rebuild trust.
(51)
Dirks et
al.(52) suggest that punishment and regulation of the transgressor have a positive
impact on trust.
Haselhuhn et al.(53) empirically show that people with incremental
beliefs regarding moral character are more likely to trust their counterpart following
trustworthy countermeasures.
In recent years, China has experienced several crises related to pandemic diseases.
For example, at the early stage of the outbreak of severe acute respiratory syndrome
(SARS) in 2003, the countermeasures by the government were unexpectedly slow and
ineffective, resulting in dramatically decreased public trust in the authorities.(47) By
contrast, during the outbreak of H1N1 in 2009, the central and local government
agencies undertook appropriate actions quickly and effectively. As a result, the
perceived efficacy of the countermeasures improved Chinese people’s trust in the
government and corresponding institutions.(54) With respect to the toxic capsule
scandal, the Chinese authorities adopted a series of countermeasures to deal with the
crisis.
According to the above discussion, we suggest that perceived efficacy of the
countermeasures has a positive influence on trust in the State FDA, trust in the
pharmaceutical companies, and trust in the pharmaceutical capsule producers during
the toxic capsule crisis.
Risk perception has been found to affect concern in a variety of contexts.(6,14,55,56)
Specifically, through a study of the public’s reactions to the Chernobyl accident,
Sjöberg(56) finds that risk is weakly positively associated with concern (e.g., worry).
By surveying a group of military sailors prospectively during an international
operation, Kobbeltved et al.(55) suggest that perceived risk has a positive impact on
6
Risk Perceptions and Behavioral Responses
concern, such as worry.
In the context of food safety, Kuttschreuter(6) provides
empirical support for a positive relationship between risk perception and concern.
Using a social-cognitive model of pandemic influenza H1N1 risk, Prati et al.(14) also
find that risk perception positively influences concern. Therefore, we propose that
risk perception has a positive influence on concern.
The level of concern plays an important role in the process of information
seeking.(57,58)
People with worry or anxiety, which may cause a feeling of
uncertainty, try to reduce the uncertainty or avoid exposure to the potential risks.(59)
Griffin et al.(60) find that, among seven effects, concern (e.g., worry) influences
people’s risk information seeking behavior. During the outbreak of the toxic capsule
crisis, an individual who had taken capsule drugs recently might have worried about
whether the capsule was toxic and how serious the harm of toxic capsules would be
for his or her health. Then the individual might have sought various ways to obtain
more information about the toxic capsule scandal and avoid the potential harm it
might cause.
Therefore, it seems plausible that concern has a positive influence on
information seeking.
Several papers have studied the information seeking process and how people
react to risk information.(21,60)
Atkin(61) posits that people pursue an amount of
certainty that will make them comfortable about relevant topics. As the uncertainty
increases, the need for information grows and thus information-seeking behavior
arises.(61,62)
On
the
other
hand,
Eagly
and
Chaiken(63)
propose
the
Heuristic-Systematic Model (HSM), suggesting that people’s desire for sufficiency is
the main driver for the information seeking process.
On the basis of Eagly and
Chaiken’s work, Griffin et al.(60) further develop the risk information seeking and
7
Risk Perceptions and Behavioral Responses
processing model by adding a variable called “information sufficiency” (i.e., the gap
between the information already held and the information needed). They find that
when the information is not sufficient, people will seek added information to cope
with the risk adequately.(60) Accordingly, we postulate that need for information has
a positive influence on information seeking.
According to the theory of planned behavior,(64-66) Griffin et al.(60) extend their
risk information seeking and processing model to investigate preventive behaviors.
Specifically, they show that an individual who seeks risk information more will
exhibit more solid risk avoidance behaviors.
Neuwirth(67) suggests that when people
are faced with information about risk severity, they are more willing to take actions to
avoid the risk. Similarly, in the context of health communication, Witte and Allen(68)
find that when people are confronted with information about risk or danger, they may
feel fearful and take adaptive risk control actions such as message acceptance and
maladaptive risk control actions such as defensive avoidance.
Therefore, we suggest
that information seeking has a positive influence on risk avoidance.
The relationship between risk perception and behavioral response to some
specific risks has been extensively studied in the literature.(36,69-71) For example,
Hammitt(69) reports that between conventional and organic produce, consumers
perceive organically grown produce as having less hazardous risk and thus are willing
Vernon(72) suggests that risk perception is
to pay significantly more to purchase it.
positively associated with preventive and protective cancer screening behavior. By
conducting a longitudinal study, Brewer et al.(73) show that the behavior motivation
hypothesis is supported, i.e., risk perception causes people to take protective actions.
Through a meta-analysis study, Brewer et al.(70) provide additional evidence for the
8
Risk Perceptions and Behavioral Responses
relationship between risk perception and behavioral response toward vaccination
against infectious disease.
Feng et al.(13) find that when people are faced with
product quality risks, they are willing to pay more to purchase better quality products
so that they can reduce or even avoid the associated risk.
Prati et al.(14) indicate that
people who have higher levels of risk perceptions of pandemic influenza H1N1 are
more likely to adopt health-related recommendations to avoid the risk. Therefore, it
is hypothesized that risk perception has a positive influence on risk avoidance.
Based on the relationships hypothesized above, we develop a conceptual model to
examine the determinants of risk perceptions and behavioral responses to the toxic
capsule crisis, which is depicted in Figure 1.
We present the methodology of the
study in the following section.
………………………………………………………………..
Insert Fig. 1 here.
………………………………………………………………..
3. METHODOLOGY
3.1 . Participants
One hundred and ninety-three undergraduate students at a Chinese university in
Shanghai participated in this study in May and June of 2012, right after the outbreak
of the toxic capsule scandal.
College student samples have been widely used in the
previous research that studies risk perceptions and behavioral responses toward
various contexts of risks.(36,35,74-76)
In addition, when college students are sick, they
are also likely to take capsule drugs by following doctors’ prescriptions and advice.
For example, in this survey, approximately 22% of the participants reported that they
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Risk Perceptions and Behavioral Responses
had taken capsule drugs in the previous six months. Thus, it is appropriate to use a
college student sample in this study.
Qualtrix.com.
Survey data were collected through
Each student who had completed the online survey received a gift for
participating.
3.2 . Instrument Development
A questionnaire was designed to measure the relationship between the nine
constructs for the conceptual model in Figure 1.
Specifically, the measures for the
constructs of risk perception, concern, and perceived efficacy of the countermeasures
were adapted from Prati et al.(14) The constructs of information seeking, need for
information and risk avoidance were assessed based on scales adapted from
Kuttschreuter’s(6) work. To measure the three constructs in terms of trust in different
stakeholders, we adapted the scales from Poortinga(42) and Kuttschreuter.(6)
Participants were asked to rate, on a seven-point Likert-type scale, how much they
agreed or disagreed with each statement in the questionnaire (i.e., 1=very strongly
disagree to 7=very strongly agree).
Before the formal study, we conducted a pilot
test, during which respondents were asked whether they could clearly understand the
questions and felt comfortable answering them.
We continued to modify the
questionnaire until it showed a fairly good content validity. Details of the
questionnaire are provided in Table II in Section 4.1.
3.3. Descriptive Statistics and Correlations
Table I presents the descriptive statistics and bivariate correlations of all the
10
Risk Perceptions and Behavioral Responses
constructs.
In particular, the participants reported high levels of concern (M=5.81),
risk perception (M=5.58), and risk avoidance (M=4.91). The levels of information
seeking (M=4.37) and need for information (M=4.12) were about average. The mean
values of the remaining constructs were all below the midpoint of four, including
perceived efficacy of the countermeasures (M=3.49), trust in the pharmaceutical
capsule producers (M=3.76), trust in the pharmaceutical companies (M=3.00) and
trust in the State FDA (M=2.82). With respect to the correlations between various
constructs, there were significantly high associations between many constructs and no
association between a few others (e.g., concern and need for information, r = 0.01).
Given that there were sufficiently high intercorrelations for several pairs of the
constructs, it is appropriate to conduct a principal component factor analysis to seek
key underlying factors, which is presented in the next section.
………………………………………………………………..
Insert Table I here.
………………………………………………………………..
4. RESULTS
4.1. Reliability and Validity Assessment
To assess the reliability and validity of the questionnaire, we first conduct a
principal component analysis (PCA) with a Varimax rotation to identify key factors
underlying all the variables in the questionnaire by using the SPSS software package.
From the PCA analysis, the variables are loaded onto the nine factors displayed in
Table II.
The eigenvalue of eight factors is greater than 1.0, and one factor has an
eigenvalue of 0.913, which is acceptable. All the factors explain approximately 77%
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Risk Perceptions and Behavioral Responses
of the total variance, which is sufficiently high to account for the observed
intercorrelations.
construct.
In addition, we calculate Cronbach’s alpha coefficients for each
All alpha scores are satisfactory, with no values less than 0.80.
Therefore, the scales of the questionnaire generally have high internal consistency
reliability.
………………………………………………………………..
Insert Table II here.
………………………………………………………………..
Then we conduct a confirmatory factor analysis (CFA) by creating a LISREL
path diagram.
The CFA shows an acceptable model fit.
The normed χ2 (χ2 to
degrees of freedom, χ2=681.44, d.f.=459) is 1.48, which is below the desired cut-off
value of 3.0. The Standardized RMR (SRMR) is 0.054, which is below the desired
cut-off value 0.10. Root mean square error of approximation (RMSEA) is 0.051,
which is lower than 0.08, indicating a good fit.
The normed fit index (NFI=0.92)
and comparative fit index (CFI=0.97) are both greater than 0.90. To summarize, the
results suggest that the structural model has a good fit.(77)
With respect to the convergent validity of the measures, first, all standardized
path loadings are greater than 0.7 except items 3 and 4 under risk avoidance (0.68 and
0.69), item 5 under trust in the State FDA (0.63) and item 1 under need for
information (0.68).
According to Kim et al.(78), standardized path loadings should be
greater than 0.7 and statistically significant.
Thus, we dropped item 5 under trust in
the State FDA from the model analysis and keep the other three items in the model
because their standardized path loadings are nearly 0.7.
that all standardized path loadings are significant.
12
In addition, t-tests reveal
Second, Cronbach’s alphas(79)
Risk Perceptions and Behavioral Responses
should be larger than 0.7.
In this study, all Cronbach’s alphas are greater than 0.8,
which satisfies the requirement. Third, the average variance extracted (AVE) for
each factor(80) should be greater than 0.5 and the composite factor reliability (CFR)(81)
should be larger than 0.7.
All AVE values are above 0.60 and the CFR is greater
than 0.80. Therefore, the results suggest there is acceptable convergent validity of
the measurement model.
To check the discriminant validity of the measures, we first perform ordinary
CFA analysis for every pair of factors, set the correlation of the two factors to 1.0, and
then test the model again.
According to Gerbing and Anderson,(82) the χ2 difference
test is used to compare the results between the constrained model and the
unconstrained model for every pair of the constructs.
In this study, the χ2 differences
are found to all be significant, which implies that the original model is better than
each constrained model.
Therefore, we establish the discriminant validity of the
measurement model.
4.2. Structural Equation Model
The conceptual model in Fig. 1 is tested using the LISREL software.
The initial
model depicted in Fig. 1 yields a good fit to the data (CFI = 0.97).1
However,
according to the Lagrange Multiplier Test (LM Test), the addition of two causal paths
significantly improves the fit of the new model, i.e., one path from trust in the
pharmaceutical companies to trust in the State FDA, and the other from trust in the
1
Note that two causal paths are found to be non-significant, i.e., one path from trust in pharmaceutical companies
to risk perception, and the other from trust in pharmaceutical capsule producers to risk perception. The results
suggest that deletion of the two paths does not change the χ2 significantly (Δχ2 (2) = 2.14, p = 0.343).
13
Risk Perceptions and Behavioral Responses
pharmaceutical capsule producers to trust in the State FDA.
Specifically, the initial
and the revised model are nested, thus, the difference in χ2 between the two models
could be used for the evaluation of the improvement in fit of the new model.(36) As
shown in Table III, the estimation of the revised model provides a significantly
improved model, i.e., the χ2 decreases significantly (Δχ2 (2) = 18.13, p < 0.001). The
results indicate that trust in the State FDA is influenced by both trust in the
pharmaceutical companies and trust in the pharmaceutical capsule producers.
In
addition, the LM Test suggests that the addition of correlated errors of measurement
provides a better fit to the data.
However, post-hoc modifications with respect to
correlated errors of indicator variables are problematic,(36,83) thus no additional
parameters are relaxed in the model.
………………………………………………………………..
Insert Table III here.
………………………………………………………………..
Fig. 2 shows the standardized LISREL path coefficients and the overall fit indices
for the test of the final model.
Table II.
The factor loadings of the final model are reported in
For the final model, the updated normed χ2 (χ2 to degrees of freedom,
χ2=675.07, d.f.=450) is 1.50, which is smaller than the desired cut-off value of 3.0.
The Standardized RMR (SRMR) is 0.067, which is below the designed cut-off value
0.10. The root mean square error of approximation (RMSEA) is 0.052, which is
lower than 0.08, indicating a good fit. The normed fit index (NFI = 0.92) and
comparative fit index (CFI = 0.97) are both greater than 0.90.
suggest that the final model fits the data quite well.
14
Thus, the results
Risk Perceptions and Behavioral Responses
………………………………………………………………..
Insert Fig. 2 here.
………………………………………………………………..
From Fig. 2, it can be seen that a small percentage of the variance in risk
perception (3.7%) is explained. Among the three different trust variables, only trust
in the State FDA (β = -0.24, t = 2.28) is found to have a significantly negative
influence on risk perception.
Trust in the pharmaceutical companies and trust in the
pharmaceutical capsule producers are both found to be insignificant predictors of risk
perception.
However, these two trust variables have an influence on trust in the
State FDA.
That is, both of them have an indirect influence on risk perception, via
trust in the State FDA.
With respect to trust, a remarkable percentage of the variance in trust in the State
FDA (51%) is explained, followed by trust in the pharmaceutical capsule producers
(25%) and trust in the pharmaceutical companies (22%). Perceived efficacy of the
countermeasures is found to be a significant determinant of trust in the State FDA (β
= 0.46, t = 5.41), trust in the pharmaceutical companies (β = 0.47, t = 5.53) and trust
in the pharmaceutical capsule producers (β = 0.50, t = 5.61), respectively.
In
addition, trust in the pharmaceutical companies (β = 0.26, t = 3.63) and trust in the
pharmaceutical capsule producers (β = 0.16, t = 2.12) explain portions of the
variance in trust in the State FDA.
About 48% of the variance in concern is explained and risk perception is found to
be a significant predictor (β = 0.70, t = 9.37). The variance of information seeking is
explained to a lesser degree (27%).
Both concern (β = 0.34, t = 4.59) and need for
information (β = 0.40, t = 5.11) are found to significantly influence information
15
Risk Perceptions and Behavioral Responses
seeking.
Finally, a considerable percentage of the variance in risk avoidance (35%)
is explained.
Information seeking (β = 0.34, t = 4.26) and risk perception (β = 0.42, t
= 5.13) are both found to be significant determinants of risk avoidance.
5. DISCUSSION
In this paper, we investigated risk perceptions and behavioral responses to the
recent outbreak of the toxic pharmaceutical capsule crisis in China. On the basis of
the previous literature, we developed a conceptual model to explore the determinants
of the public risk perceptions of the crisis and reactions to the crisis.
An online
survey was conducted to collect the data and test the conceptual model.
In general,
we found that participants did not trust the three major stakeholders during the crisis,
including the State FDA of China, pharmaceutical companies, and pharmaceutical
capsule producers.
In addition, they perceived the countermeasures by the
authorities to be relatively ineffective, i.e., people were generally not satisfied with
the actions adopted by the government and corresponding agencies. Participants
reported fairly high levels of perceived risk of the toxic capsules and concern about
the risk. They had high levels of risk avoidance, i.e., they were willing to take
actions to reduce the risk associated with toxic capsules. There were moderate levels
of need for information and information seeking.
We use the structural equation modeling method to test the proposed conceptual
model and explore the relationships between the variables. The results suggest that
the model depicted in Fig. 2 yields a good fit to the data.
One of the most interesting
results of this study is that among the three different trust variables, only trust in the
16
Risk Perceptions and Behavioral Responses
State FDA is found to be a significant determinant of risk perception for toxic
capsules, and the other two trust variables influence trust in the State FDA, rather than
risk perception directly.
As discussed previously, three major stakeholder groups are
involved in the toxic capsule crisis.
One is the pharmaceutical capsule producers
which used industrial gelatin made from discarded leather to produce capsules and
then sold them to pharmaceutical companies. The second one is the pharmaceutical
companies which used toxic capsules to encapsulate drugs during their manufacturing
process.
The third stakeholder is the State FDA of China which is responsible for
protecting and promoting public health through the regulation and supervision of food
and drug safety in China. To compare the impact of trust in those three different
organizations on risk perception of toxic capsules, we incorporated three trust
variables in our model.
Following the literature,(6,36,41) we hypothesized that risk
perception is negatively related to each of the three variables, i.e., higher levels of
trust in an organization generally leads to lower levels of risk perception.
Surprisingly, the results suggest that only trust in the State FDA dampens risk
perception of the toxic capsules, whereas trust in the pharmaceutical capsule
producers and trust in the pharmaceutical companies have an indirect influence on
risk perception via trust in the State FDA. We provide a possible explanation as
follows. From the media reports, the ostensible cause of the toxic capsule crisis is
that some firms illegally used industrial gelatin to produce capsules, and
pharmaceutical companies might have intentionally purchased what turned out to be
toxic capsules for the sake of cost reduction.
However, the crisis revealed the
regulatory gaps in the drug industry oversight by the State FDA of China, i.e., the
current regulation and supervision rules for drug safety are far from perfect.
17
Such
Risk Perceptions and Behavioral Responses
imperfect regulation and supervision rules were arguably seen by the Chinese public
as the root cause of the toxic capsule scandal.
Because the public thought that the
State FDA of China was mainly responsible for the crisis, they had lower levels of
trust in the State FDA, resulting in higher levels of risk perception of toxic capsules.
This is in line with the findings of the prior studies which investigated risk perception
of pandemic diseases in China, such as SARS and H1N1.(47,84) In addition, the State
FDA supervises and regulates the pharmaceutical industry, including the
pharmaceutical companies and pharmaceutical capsule producers.
It is intuitive that
the two trust variables have a positive influence on trust in the State FDA.
Therefore,
the major insight of this result is that to reduce the public’s risk perception of drug
safety in developing countries where the regulation rules or policies are not perfect, a
potentially effective risk communication strategy might be to improve the regulation
and supervision system and thus enhance public trust in the official agencies.
Perceived efficacy of the countermeasures by the authorities has a positive impact
on all three trust variables in the context of the toxic capsule scandal.
This is
consistent with the consequences of several previous major pandemic diseases in
China.
For example, the SARS epidemic originated from Southern China in
November 2002, however, the Chinese government did not report its outbreak to the
World Health Organization (WHO) until February 2003.(85)
Due to a lack of
openness, insufficient and delayed efforts had been devoted to control the spread of
the epidemic at the early stages in China.(85) This in turn resulted in overwhelmingly
lower levels of the public’s trust in the authorities during the outbreak of SARS.(47,49,54)
In addition, trust is fragile, and once trust is destroyed, it is very difficult and
time-consuming to rebuild.(44) In the case of the toxic capsules, the mean value of
18
Risk Perceptions and Behavioral Responses
the perceived efficacy of the countermeasures is below the midpoint four, which
implies that the public was not satisfied with the actions implemented by the
authorities.
This suggests that at the very early stage of the crisis, the authorities
should have adopted timely and effective actions to improve people’s trust in the
government agencies and corresponding organizations in the pharmaceutical industry.
Furthermore, we observed that there is some difference in the degree of the
impact of perceived efficacy of the countermeasures on the three trust variables.
Specifically, perceived efficacy of the countermeasures has the largest effect on trust
in the State FDA, compared to trust in capsule producers and trust in pharmaceutical
companies. This is an intuitive result because the State FDA is an agency of the
Chinese Ministry of Health, and is the most representative authority undertaking
countermeasures during the crisis.
The relationship between risk perception and concern has been widely
documented in the literature.(6,14,55,56) Specifically, when studying the predictors of
responses to food risk messages, Kuttschreuter(6) showed that risk perception has a
weakly positive impact on concern. The impact was reported to be fairly strong in
the context of pandemic influenza H1N1.(14)
In line with these studies, we found that
the perceived risk level had a strong influence on concern in the toxic capsule case.
Therefore, it seems plausible to conclude that risk perception is an important
determinant of concern in a variety of risky situations, including pandemic diseases,
food and drug safety risks.
To further investigate the potential difference in the degree of the influence of
risk perception on concern among different health risks, a more general conceptual
model could be developed and tested in future studies, based on prior studies and this
19
Risk Perceptions and Behavioral Responses
research.(6,14,86)
In such a general model, for each specific risk (e.g., food safety risk,
pandemic influenza H1N1 risk, or toxic drug capsule risk), risk perception and
concern would be determinants of behavioral responses to that risk.
Both risk
perception and concern would be influenced by cognitive (e.g., trust, perceived
coping efficacy, etc.) and social-contextual factors (e.g., perceived governmental
preparedness, level of development in country, etc.).
In addition, under some
circumstances, cognitive and social contextual factors might have a direct influence
on behavioral responses, and background levels of other risks might affect perception
of a specific risk.
It is beyond the scope of this research to create and test such a
general model considering several risks.
Both concern and need for information were found to be significant determinants
of information seeking in terms of the toxic capsule crisis.
Note that the relationship
between concern and information seeking was shown to be insignificant for the risk
associated with a potential Salmonella or dioxin contamination of chicken in
Kuttschreuter.(6)
This suggests that concern significantly influences information
seeking in the context of drug safety, but this may not be true in the context of food
safety. On the other hand, according to the risk information and processing model
by Griffin et al.,(60) the need for information is a key determinant of information
seeking.
For the public, the risk of toxic capsules was fairly novel.
As a result,
information insufficiency would induce people to seek information so that they could
better deal with the risk of toxic capsules.
Our results show that risk avoidance is predicted by both risk perception and
information seeking with respect to the risk of toxic capsules. The prior literature
suggests that risk perception is central to health behavior theories.(36,69-71)
20
Our
Risk Perceptions and Behavioral Responses
results conform to the health behavior theories in the sense that risk perception also
has a significant positive impact on health behaviors in the context of drug safety risks.
On the other hand, information seeking is found to be significantly positively related
to risk avoidance when people were faced with the toxic capsule crisis.
For example,
for those who had to take capsule drugs, they could check online for the batch
numbers of products found with excessive levels of chromium released by the State
FDA and decide whether they needed to change the medicine.(3)
Going to an
extreme, to avoid the risk of ingesting toxic capsules, some Chinese consumers
creatively worked out a 4-step do-it-yourself tutorial of how to wrap medicine by
using a warm steamed bun to replace the capsule, and posted it on Sina’s Weibo.com,
receiving tens of thousands of retweets within a day.(87)
This study has several limitations. First, a student sample is used in this study.
As discussed previously, it is appropriate to use college students to investigate risk
perception and behavioral response to the risk of toxic capsules. However, there
might be some difference between students and the general public, though we believe
that it does not make the student sample less appropriate for our study.
Second, the results suggest that the final model provides a good fit to the data.
However, this does not imply that this is the only model that fits the data. Future
research could test rival models that might better explain the data.
Finally, an advantage of this study is that we focus on a parsimonious model
which considers the primary relationships between the variables. However, a more
general model may be considered in future studies.
Such a more general model
might have a higher explained variance in risk perception.
Previous studies show
that in addition to trust, risk perception can be affected by other factors, such as
21
Risk Perceptions and Behavioral Responses
contemporary world views,(36) susceptibility to risk,(6) media exposure,(88) and
mortality and morbidity risks to sensitive populations and perceived controllability by
individuals or institutions.(89) Similarly, this study only considers perceived past
performance (i.e., perceived efficacy of countermeasures) as a determinant of trust.
According to the Trust, Confidence and Cooperation (TCC) model, both perceived
past performance and perceived value similarity may influence trust.(90,91)
In
addition, Barber(92,93) argues that two factors constitute trust: the expectation of
technical competence and the expectation of fiduciary responsibility.
could examine the levels of these two components of trust.
Future studies
For example, to enhance
trust, the State FDA could exhibit both technical competence and use its funds
responsibly.
Another example is that in this study, we only consider risk perception
and information seeking as the determinants of risk avoidance.
The classical
Protection Motivation theory posits that risk avoidance can be influenced by a variety
of factors, including the perceived severity of a risk, the perceived probability of the
occurrence, the efficacy of the recommended preventive behavior, and the perceived
self efficacy.(94)
It would be interesting to incorporate some of those variables
discussed above into a more general model to better explain risk perceptions and
behavioral responses to the toxic capsule crisis in China.
Acknowledgments
We thank the area editor Michael Siegrist and two anonymous referees for their
thoughtful and constructive reviews, which have helped significantly improve the
article. Portions of this work were supported by grants to L. Robin Keller from the
John S. and Marilyn Long U.S. - China Institute for Business and Law at the
University of California, Irvine, and Tianjun Feng from the National Natural Science
Foundation of China (Grant 70901022), the Shanghai Philosophy and Social Science
Planning Funds (Grant 2012BGL014), and the Ministry of Education of China (Grant
for Overseas-Returnees).
22
Risk Perceptions and Behavioral Responses
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27
Risk Perceptions and Behavioral Responses
Appendix
Trust in the
State FDA
Perceived
Efficacy of
Countermeasures
Risk
Perception
Risk
Avoidance
Trust in the
Pharmaceutical
Companies
Concern
Information
Seeking
Trust in the
Pharmaceutical
Capsule Producers
Need for
Information
Fig. 1. Hypothesized model of risk perceptions and behavioral responses in the toxic
drug capsule crisis
28
Risk Perceptions and Behavioral Responses
Table I. Descriptive Statistics and Intercorrelations of the Constructs
M
S.D.
1
2
3
1. Risk perception
5.58 1.24
2. Concern
5.81 1.23
0.69***
3. Risk avoidance
4.91 1.50
0.49*** 0.44***
4
4. Trust in the pharmaceutical
3.76 1.18
capsule producers
-0.01
-0.16
-0.06
5. Trust in the pharmaceutical
3.00 1.32
companies
0.03
-0.09
0.01
0.47***
5
6
6. Trust in the State FDA
2.82 1.21
-0.15*
-0.16*
0.05
0.52*** 0.54***
7. Perceived efficacy of the
countermeasures
3.49 1.33
-0.02
-0.08
0.10
0.47*** 0.43*** 0.66***
8. Information seeking
4.37 1.31
0.24**
0.33*** 0.43*** 0.08
9. Need for information
4.12 1.69
0.04
0.01
0.10
Note: *p < 0.05; **p < 0.01; ***p < 0.001.
29
0.11
0.19*
7
8
0.34***
0.47*** 0.43*** 0.39*** 0.62*** 0.39***
9
Risk Perceptions and Behavioral Responses
Table II. Factor Loading Estimates for Indicator Variables
Factor
loading
Factors/Variables
F1
Risk perception
V1
V2
V3
V4
Toxic capsules have adverse effects on human health.
The harmful ingredients that toxic capsules contain affect curative effects of the drugs.
The harmful ingredients that toxic capsules contain cause permanent damage to human health.
The harmful ingredients that toxic capsules contain increase the chance of having other diseases.
The harmful ingredients that toxic capsules contain cause damage to some organs of human
V5
body.
F2
Toxic capsules are produced by only a small percentage of capsule producers, and most capsule
producers are trustable.
V2 Those capsule drugs that are not released by the State FDA online are safe and reliable.
V3 Most capsules in the market are safe and reliable.
V1
The pharmaceutical companies are innocent. Purchasing toxic capsules is the individual
behavior of the employees in the procurement department of the companies.
The relevant pharmaceutical companies are innocent. They purchased toxic capsules from
V2
capsule producers without knowing they are toxic.
V1
V2
V3
V4
0.92
0.91
0.78
0.74
0.82
0.68
0.69
0.70
0.75
0.85
Trust in the pharmaceutical companies
V1
F6
0.87
Risk avoidance
V1 I try to avoid the consumption of capsule drugs unless I have to.
I will not purchase any capsule drugs and use non-capsule drugs instead if necessary in the
V2
coming a few months.
V3 When taking capsule drugs, I will open the capsule and consume the ingredients inside capsules.
Before taking capsule drugs, I will check the product batch number with excessive levels of
V4
chromium released by the State FDA online and decide whether to consume them.
F4 Trust in the pharmaceutical capsule producers
F5
0.87
Concern
V1 If I have taken capsule drugs recently, I will feel worried about my health.
If I have taken drugs related to toxic capsules recently, I will feel afraid that the harmful
V2
ingredients the toxic capsules contain affect my health.
V3 If my family or friends have taken capsule drugs recently, I will feel worried about their health.
If a pregnant woman who I know has taken capsule drugs recently, I will feel worried about the
V4
health of her baby.
F3
0.83
0.75
0.76
0.85
0.85
0.91
Trust in the State FDA
The regulation rules of drug safety are well developed in China.
The regulation and supervision of drug safety is sufficient.
The drug quality inspection technique is reliable.
The State FDA of China is well prepared for any drug safety problems.
0.90
0.92
0.85
0.91
F7 Perceived efficacy of the countermeasures
V1
The Chinese government and corresponding agencies have dealt with the toxic capsule crisis
promptly and effectively.
30
0.86
Risk Perceptions and Behavioral Responses
V2 The recall of toxic capsule drugs is reliable and timely.
The countermeasures dealing with the toxic capsule crisis can prevent the outbreak of similar
V3
crises.
F8
0.80
Information seeking
After the outbreak of the toxic capsule crisis, I searched for detailed information about the crisis
immediately.
When it comes to drug safety, I will search for the latest news about the regulation and
V2
supervision of drug safety.
Before taking capsule drugs, I will search for relevant information to decide whether they are
V3
safe for use.
V1
F9
0.85
0.76
0.96
0.81
Need for information
V1 The public media reported the toxic capsule scandal promptly.
V2 The reports of the toxic capsule scandal by the public media are objective and reliable.
The product batch number with excessive levels of chromium reported by the public media is
V3
sufficient.
V4 I can conveniently get the information on the toxic capsule scandal which I need.
31
0.68
0.80
0.82
0.73
Risk Perceptions and Behavioral Responses
Table III. Test Statistics for Hypothesized Model
Model
χ2
df
CFI
Initial
693.20
452
0.97
Addition of two significant paths a
675.07
450
0.97
Δχ2
Δdf
18.13
2
Note. CFI = comparative fit index.
Trust in the pharmaceutical companies  trust in the State FDA, trust in the
pharmaceutical capsule producers  trust in the State FDA.
a
32
Risk Perceptions and Behavioral Responses
(R2=0.037)
Trust in the
State FDA
0.46***
Perceived
Efficacy of
Countermeasures
-0.24**
(R2=0.51)
0.50***
Trust in the
Pharmaceutical
Companies
(R2=0.35)
0.42***
0.26***
0.47***
Risk
Perception
N.S.
0.70***
0.16*
N.S.
Risk
Avoidance
0.34***
Concern
0.34***
(R2=0.22)
Information
Seeking
2
(R =0.48)
0.40***
Trust in the
Pharmaceutical
Capsule Producers
Need for
Information
(R2=0.27)
(R2=0.25)
Note: *: p < 0.05, t > 1.96; **: p < 0 .01, t > 2.58; ***: p  0.001, t > 3.29.
Fig. 2. Results of the testing of the conceptual model (Chi-square = 675.07, d.f. = 450,
p = 0.000, RMSEA = 0.052)
33