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Dengetal. Antimicrob Resist Infect Control (2021) 10:97
https://doi.org/10.1186/s13756-021-00966-z
RESEARCH
Predictors ofphysicians’ intentions touse
clinical practice guidelines onantimicrobial
intertiary general hospitals ofChina:
astructural equation modeling approach
Qingwen Deng, Zhichao Zeng, Yuhang Zheng, Junhong Lu and Wenbin Liu*
Abstract
Background: With inappropriate use of antimicrobials becoming a great public health concern globally, the issue
of applying clinical practice guidelines (CPGs) to regulate the rational use of antimicrobials has attracted increasing
attention. Taking tertiary general hospitals in China for example, this study aimed to identify factors to investigate the
comprehensive influencing mechanism for physicians’ intention to use CPGs on antimicrobials.
Methods: Based on the integration of Theory of Planned Behavior (TPB), Technology Acceptance Model (TAM), and
Technology-Organization-Environment framework (TOE), a questionnaire survey was conducted covering potential
determinants of affecting physicians’ intentions to use CPGs on antimicrobials at the individual level (attitude, subjec-
tive norms and perceived risk), technical level (relative advantage and ease of use), and organizational level (top man-
agement support and organizational implementation). Data were collected from 644 physicians in tertiary general
hospitals in eastern, central and western China, which were obtained by multi-stage random sampling. The structural
equation modeling (SEM) was used to link three-level factors with physicians’ behavioral intentions.
Results: The majority of the participants (94.57%) showed a positive tendency toward intention to use CPGs on
antimicrobials. The reliability and validity analysis showed the questionnaire developed from the theoretical model
was acceptable. SEM results revealed physicians’ intentions to use CPGs on antimicrobials was associated with attitude
(β = 0.166, p < 0.05), subjective norms (β = 0.244, p < 0.05), perceived risk (β = − 0.113, p < 0.05), relative advantage
(β = 0.307, p < 0.01), top management support (β = 0.200, p < 0.05) and organizational implementation (β = 0.176,
p < 0.05). Besides, subjective norms, perceived risk, relative advantage, ease of use, and top management support
showed their mediating effects from large to small on the intentions, which were 0.215, 0.140, 0.103, 0.088, − 0.020,
respectively.
Conclusions: This study revealed the significance of multifaceted factors to enhance the intention to use CPGs on
antimicrobials. These findings will not only contribute to the development of targeted intervention strategies on
promoting the use of CPGs on antimicrobials, but also provide insights for future studies about physicians’ adoption
behaviors on certain health services or products.
Keywords: Antimicrobials, Clinical practice guidelines, Structural equation modeling, Utilization, China
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Open Access
*Correspondence: wenbinliu126@126.com
School of Public Health, Fujian Medical University, Room 108 in the
Building for School of Public Health, No.1 Xuefubei Road, Minhou District,
Fuzhou 350122, China
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Dengetal. Antimicrob Resist Infect Control (2021) 10:97
Background
Antimicrobials, which have been critically important in
the evolution of medical treatment, effectively reduces
the morbidity and mortality from infections [1]. How-
ever, the spread of inappropriate use of antimicrobials
has driven the emergence of antimicrobial resistance
(AMR), which is a widely acknowledged threat to global
health and sustainable development [2]. It leads to weak-
ened effectiveness and persistent infections [3] that will
greatly undermine our ability to fight infectious disease,
resulting in negative consequences at the individual and
societal levels [4], such as longer hospital stays, higher
medical costs, poor patient outcomes and waste of health
resources. More than 20 billion dollars in the American
health system and over 700,000 deaths worldwide were
linked to AMR in 2016 [5]. e World Bank estimates
that AMR might put 28 million people in an extremely
poor situation by 2050, and loss of the global gross
domestic product caused by AMR would be close to the
2008 global financial crisis [6].
To avoid further deteriorations caused by AMR and
improve outcomes of antimicrobials, many countries
have launched clinical practice guidelines (CPGs) on
antimicrobials, which provide recommendations for phy-
sicians based on the current best evidence. As reported
by the American Institute of Medicine [7], CPGs have
played an important role in standardizing clinical treat-
ment behaviors, improving the quality of medical ser-
vices, and promoting patients’ health. Although clear
principles had been established with significant effec-
tiveness of CPGs well proved, the expansion of regula-
tion implementation was still halted with poor adherence
to regarding guidelines. is situation was outstanding
especially in many developing countries, where antimi-
crobials consumption doubled between 2000 and 2015
[8]. For instance, in China, one of the world’s largest con-
sumers of antimicrobials for human health [9], the inap-
propriate use of antimicrobials is still striking even after
the launch of Guiding Principles for Clinical Application
of Antimicrobials in 2015 [10].
Given the severe situation of AMR worldwide and
guidelines’ contributing role of improving service qual-
ity and patients’ health, the key point of improving the
AMR issue is that the appropriate use of antimicrobials
could be regularized by the use of CPGs on antimicro-
bials [11]. Efforts have been made to understand which
factors could predict physicians’ antimicrobials pre-
scribing using various behavioral theories, such as the
eory of Planned Behavior (TPB), the knowledge-atti-
tude-practice (KAP) model, the Technology Acceptance
Model (TAM), and the Technology-Organization-Envi-
ronment framework (TOE). e focus of these theo-
ries varies from the individual to the technical to the
organizational environment. However, despite a few
studies have considered the influencing factors from
different levels of prescribing behavior [2], most of the
current studies were fragmented and focused on only
one aspect of the determinants. For example, many
studies have investigated health professionals’ beliefs
and practices from the individual level [12–16]. And
more importantly, our understanding on physicians’
actual intentions of using CPGs on antimicrobials and
its influencing factors is still limited. As key stakehold-
ers in clinical practice, it’s necessary to understand phy-
sicians’ beliefs and uses of CPGs on antimicrobials and
reasons for using or not using it if we did attempt to
promote the appropriate use of antimicrobials [1, 17].
While to some extent, behavioral intention figures a
proxy role on actual behaviors [18]. If individuals show
a positive or negative intention, we presume that they
would tend to use or not use a specified technology or
other products. erefore, we targeted physicians in
tertiary general hospitals, aimed to establish a model
that integrated from TPB, TAM and TOE for determin-
ing physicians’ intentions to use CPGs on antimicrobi-
als and its influencing factors. e findings can not only
serve as evidence to better AMR control via the pro-
motion of the use of CPGs on antimicrobials, but also
provide a feasible reference for future research on the
influencing factors of physicians’ intention or behaviors
on utilizing certain health services or products.
Methods
Study setting
is study was conducted in tertiary general hospitals
in China. Although the regulation policy for the clinical
application of antimicrobials covers all levels of medical
institutions, for the weakness of the primary medical ser-
vices system in China, the provision of vast medical ser-
vices is heavily dependent on hospitals, especially tertiary
hospitals. In 2019, tertiary hospitals received 1.77 billion
medical visits [19]. As one of the major consumers of
antimicrobials, the irrational use of antimicrobials in ter-
tiary hospitals is quite prominent. us, it’s necessary to
regulate the use of antimicrobials of physicians in tertiary
hospitals for reducing AMR.
Theoretical framework
e theoretical framework (Fig. 1) was adapted from
the integration of TPB, TAM and TOE to illuminate the
determinants of physicians’ intentions to use CPGs on
antimicrobial from three levels, namely individual level
(physicians), technical level (CPGs on antimicrobial), and
organizational level (hospitals).
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Dengetal. Antimicrob Resist Infect Control (2021) 10:97
Individual‑level factors
Proposed by TPB, behavioral intention is a function of
three factors, including attitude, subjective norms and
perceived behavioral control [20]. Attitude is defined as
a positive or negative evaluation of a particular behavior
[21], many studies showed a strong correlation between
attitude and intention [22, 23]. Subjective norms are
kinds of perceived criteria and social pressure to engage
or not to engage in behavior [24], which may also sig-
nificantly affect physicians’ intentions. Also, perceived
behavioral control reflects the person’s belief that an
action is under his or her control, such as perceived risk.
Risk perception is associated with low intentions.
Technical‑level factors
Proposed by TAM, the relative advantage is a degree to
which new technology or product is more advantageous
than the original or competing ones [25], while ease of
use is a degree to which the potential user expects the
product can perform with ease [26, 27]. Regarding the
intentions to use CPGs, the physicians and managers are
more inclined to adopt the guidelines having better out-
comes and efficiency with no additional effort and time
to learn how to implement.
Organizational‑level factors
TOE suggests top management support “can foster inno-
vation by creating an organizational context that wel-
comes change and is supportive of innovations” [28]. In
hospitals, top management’s involvement in the use of
CPGs on antimicrobials through formal measures (e.g.
funding, training, and system building), can ensure the
accomplishment of intended outcomes to a great extent
[29]. Organizational implementation refers to the whole
implementation process of CPGs on antimicrobials,
including providing relevant information, supervision,
and inspection, corrective feedback, respectively [30, 31].
Measurements
Based on the theoretical model, as well as the literature
review of previous studies, a questionnaire with 30 items
was developed for this study (Additional file 1). ree
items in Part 1 were used to measure the intentions to
use CPGs on antimicrobials of physicians. ere were
21 items in Part 2, covering seven potential factors: atti-
tude, subjective norms, perceived risk, relative advantage,
ease of use, top management support and organizational
implementation. Each item in Part 1&2 corresponding
to the constructs was measured using a five-point Likert
scale, where 1 = Strongly disagree, 2 = Disagree, 3 = Neu-
tral, 4 = Agree, and 5 = Strongly agree. And Part 3 was a
personal information card consisted of 6 items, includ-
ing several basic characteristics of participants like gen-
der, age, education, professional degree, department, and
years in practice.
Sampling
Considering the diverse level of socio-economic devel-
opment in different regions of China, a cross-sectional
survey was conducted using a multistage sampling strat-
egy. Firstly, Fujian, Hubei, Yunnan & Sichuan provinces
were randomly selected respectively on behalf of eastern,
central and western regions of China. Secondly, 4 tertiary
general hospitals were selected from each of the selected
regions. Lastly, in each selected hospital, 16–20 physi-
cians were randomly sampled from major departments
Fig. 1 The theoretical framework
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Dengetal. Antimicrob Resist Infect Control (2021) 10:97
of internal medicine and surgery, respectively. And 3–5
physicians were randomly sampled from departments of
gynecology and obstetrics, ophthalmology and otorhino-
laryngology, orthopedics, and others, respectively. us,
50–60 physicians from each hospital were invited to par-
ticipate in the survey.
Data collection
A cross-sectional questionnaire survey was performed to
investigate the determinants of physicians’ intentions to
use CPGs on antimicrobials in China. With the support
of sampled hospitals, each round for filling out the ques-
tionnaire was accompanied by trained facilitators. e
purpose of the study and the use of data will be explained
in detail to ensure the participants understand what they
needed to do and how to do it. All responses were anony-
mous, filled out by the participants at their convenience
and returned directly to the researchers.
Data collection started from April 2018 and lasted for
nearly one year. Overall, a total of 676 questionnaires
were returned. After excluding responses that (1) pro-
vided the same response for all items, (2) incomplete
questionnaires, we obtained 644 valid questionnaires
with a valid response rate of 95.27%.
Data analysis
is study used SPSS 21.0 and AMOS 17.1 software pro-
grams as the two main statistical tools to analyze the data.
To analyze the descriptive data and investigated variables
clearly, several steps were followed. Firstly, descriptive
statistics were performed for the analysis of participants’
distribution characteristics. Secondly, we conducted the
assessment of reliability and validity via Cronbach’s α
Coefficient and factor analysis to tell whether the ques-
tionnaire was acceptable. Finally, structural equation
modeling (SEM) was used to analyze the mechanism and
the relationship between the factors via path analysis and
mediating effect test. e path coefficients calculated by
path analysis are equivalent to the standardized regres-
sion coefficients and direct effects. e mediating effects
(indirect effects) and total effects were obtained by medi-
ating effect test. e indirect effects refer to the influence
of one variable on another through a third variable, and
its value was calculated through the Bootstrap method.
If the value does not contain zero in its 95% confidence
interval, the mediating effect is considered significant
[32].
Results
Descriptive characteristics
A total of 644 physicians were included in this study.
Among the participants, 54.50% (n = 351) were males and
45.50% (n = 293) were females. Most participants were in
the age group of under 35years old (55.75%, n = 359),
followed by 35–44years old (34.63%, n = 223). In terms
of educational level, 98.91% (n = 637) reported having a
bachelor’s degree or above. e proportion of the partici-
pants with the professional titles of junior, intermediate,
senior was 38.82%, 38.35%, 22.83%, respectively. Nearly
90% of the participants had less than 15years of prac-
tice experience. And about a third of participants were
from the region of the east, central and west, respectively
(Table1).
Reliability andvalidity
Table2 reports Cronbach’s alpha, composite reliability
(CR), and the average variance extracted (AVE) of all
constructs. e Cronbach’s alpha of 8 constructs and
the whole questionnaire were all greater than the rec-
ommended threshold of 0.7 [33], ranging from 0.810
to 0.885, suggesting internal consistency can be con-
sidered adequate. Besides, all factor loading values of
items were above the acceptability value of 0.5 [34].
Table 1 Demographic characteristics of participants
Variable Category Frequency Percentage (%)
Gender Male 351 54.50
Female 293 45.50
Age < 35 years old 359 55.75
35–44 years old 223 34.63
≥ 45 years old 62 9.63
Education Junior college or
below 7 1.09
Bachelor 218 33.85
Master 342 53.11
Doctor 77 11.96
Professional title Junior 250 38.82
Intermediate 247 38.35
Senior 147 22.83
Department Internal medicine 233 36.18
Surgery 188 29.19
Gynecology and
obstetrics 57 8.85
Ophthalmology and
otorhinolaryngology 65 10.09
Orthopedics 44 6.83
Other 57 8.85
Years in practice < 5 years 225 34.94
5–10 years 192 29.81
11–15 years 162 25.16
16–20 years 59 9.16
> 20 years 6 0.93
Region East 217 33.70
Central 210 32.61
West 217 33.70
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Moreover, the CR scores and AVE values of all con-
structs were above the recommended value of 0.7 [35]
and 0.5 [36], respectively, which indicated a good con-
vergent validity.
en, we followed Fornel and Larcker’s (1981) sugges-
tion [34] to calculate the square root of AVE. As shown
in Table3, the square root of AVE (reported in the diago-
nal of correlation matrix) of each construct is higher than
the correlation coefficients of any construct with other
constructs, which means the discriminant validity is
acceptable.
Intentions touse CPGs onantimicrobials andmeasurement
scores ofparticipants
A high intention to use CPGs on antimicrobial in clinical
practice (Mean = 4.12, SD = 0.58) were evident (Table4).
e overwhelming majority (94.57%) scored above neu-
tral, and 33.39% of the intention scores were greater
Table 2 Results of reliability and convergent validity analyses
Construct Item Factor loading Cronbach’s α AVE CR
Attitude ATT1 0.712 0.862 0.632 0.837
ATT2 0.808
ATT3 0.858
Subjective norms SN1 0.776 0.876 0.707 0.879
SN2 0.864
SN3 0.879
Perceived risk PR1 0.699 0.810 0.593 0.813
PR2 0.808
PR3 0.799
Behavioral intention BI1 0.766 0.859 0.610 0.824
BI2 0.810
BI3 0.766
Relative advantage RA1 0.779 0.854 0.666 0.857
RA2 0.835
RA3 0.833
Ease of use EOU1 0.806 0.869 0.692 0.870
EOU2 0.865
EOU3 0.823
Top management support TMS1 0.785 0.837 0.627 0.834
TMS2 0.745
TMS3 0.842
Organizational implementation OI1 0.839 0.885 0.728 0.889
OI2 0.898
OI3 0.821
The whole questionnaire 0.885
Table 3 Results of discriminant validity analysis
Construct PR SN EOU RA TMS AT T OI BI
PR 0.770
SN 0.000 0.841
EOU 0.000 0.000 0.832
RA 0.000 0.000 0.671 0.816
TMS 0.000 0.000 0.588 0.644 0.792
ATT − 0.119 0.619 0.198 0.335 0.208 0.795
OI 0.000 0.000 0.468 0.513 0.597 0.166 0.853
BI − 0.133 0.347 0.438 0.581 0.571 0.504 0.519 0.781
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Dengetal. Antimicrob Resist Infect Control (2021) 10:97
than average. e attitudes of the participants showed a
strong tendency in favor of the use of CPGs on antimi-
crobials (M = 4.29, SD = 0.56). eir perceived pressure
(subjective norms) from influential people was relatively
high (Mean = 4.16, SD = 0.59), while their perceived risk
of using CPGs on antimicrobials was found to be low
(Mean = 2.23, SD = 0.85). Most participants, specifically,
87.42% and 84.16% felt positive in relative advantage
(Mean = 3.96, SD = 0.67) and ease of use (Mean = 3.84,
SD = 0.66), respectively. e scores of top management
support (Mean = 4.01, SD = 0.61) and organizational
implementation (Mean = 4.05, SD = 0.60) portrayed the
participants’ appreciation of the organizations’ readiness
to use CPGs on antimicrobials.
Structural equation modeling
A favorable fitness of data into the theoretical frame-
work was found: χ2/df = 3.736 (< 5), GFI = 0.900 (> 0.9),
AGFI = 0.873 (> 0.85), CFI = 0.933 (> 0.9), N FI = 0.911
(> 0.9), IFI = 0.933 (> 0.9), RMSEA = 0.065 (< 0.08),
which demonstrated the research model has fit the data
well.
e final structural model with the standardized esti-
mates among the constructs is presented in Fig.2 and
Table 5. Totally 78.89% of the variance was explained
by the model. Regarding the determinants of physi-
cians’ intentions to use CPGs on antimicrobials, the
model indicated that, at the individual level, an atti-
tude in favor of CPGs on antimicrobials was associated
with higher intentions to use CPGs on antimicrobi-
als (β = 0.166, p < 0.05). Subjective norms predicted
physicians’ intentions to use CPGs on antimicrobials
(β = 0.244, p < 0.05). Greater perceived obstacles and
risks were linked to lower intentions to use CPGs on
antimicrobials (β =—0.113, p < 0.05). At the technical
Table 4 Measurement scores of the participants
SD Standard deviation
Measurements Mean SD Skewness Median N (%) of scores > 3
Intention 4.12 0.58 − 0.489 4 609 (94.57)
Attitude 4.29 0.56 − 0.268 4 625 (97.05)
Subjective norms 4.16 0.59 − 0.250 4 601 (93.32)
Perceived risk 2.23 0.85 0.700 2 89 (13.82)
Relative advantage 3.96 0.67 − 0.107 4 563 (87.42)
Ease of use 3.84 0.66 − 0.229 4 542 (84.16)
top management support 4.01 0.61 − 0.312 4 587 (91.15)
organizational implementation 4.05 0.60 − 0.275 4 591 (91.77)
Fig. 2 Determinants of physicians’ intentions to use CPGs on antimicrobials. *p < 0.05; **p < 0.01; ***p < 0.001
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Dengetal. Antimicrob Resist Infect Control (2021) 10:97
level, better performance in relative advantage was
associated with higher intentions to use CPGs on anti-
microbials (β = 0.307, p < 0.01), while the impact of ease
of use on attitude toward CPGs on antimicrobials was
not significant (β =—0.050, p > 0.05), and the direct
influence of ease of use on the intentions to use CPGs
on antimicrobials was not found. At organizational-
level, top management support (β = 0.200, p < 0.05)
and organizational implementation (β = 0.176, p < 0.05)
were linked to stronger intentions to use CPGs on
antimicrobials.
On the whole, relative advantage figured the strongest
direct and total effects on intention (0.307/0.522), fol-
lowed by subjective norms (0.244/0.347) and top man-
agement support (0.200/0.340). Additionally, significant
mediating effects were also found in the model. Except
that attitude and organizational implementation have
no mediating effect on behavioral intention, other con-
structs mediated the significant effects on the relation-
ship between them. Among them, relative advantage
exerted the strongest indirect effects on intention (0.215),
followed by top management support (0.140), subjec-
tive norms (0.103), ease of use (0.088) and perceived risk
(− 0.020).
Discussion
Main ndings
is study revealed that physicians in tertiary general
hospitals of China have high intentions to use CPGs on
antimicrobials, with relatively favorable evaluations and
perceptions on CPGs on antimicrobials. e integrated
model of TPB, TAM and TOE fits well with the data:
intentions to use CPGs on antimicrobials are directly or
indirectly predicted by the attitudes, subjective norms,
perceived risk, relative advantage, ease of use, top man-
agement support and organizational implementation.
Comparison withother studies
Eects ofindividual‑level factors
Consistent with previous studies [37–41], attitude and
subjective norms are important factors that have a direct
positive influence on physicians’ intentions to use CPGs
on antimicrobials. In the field of health care, the attitude
and subjective norms of health professionals are often
highlighted as they related to a sense of security in spe-
cific behaviors [42], and are shaped in part by perceived
external pressures on them. Perceived risk has a nega-
tive impact on physicians’ intentions to use CPGs on
antimicrobials. e assumption and perception of vari-
ous potential risks (such as income reduction, failure in
disease control, and patient dissatisfaction) in the imple-
mentation process may hinder the occurrence of behav-
iors. In addition to the direct impacts, both subjective
norms and perceived risk have indirect effects on inten-
tions through attitude. us, we need to pay attention to
the various linking effects of other associated factors if
we want to improve the effect of attitude on intentions.
Eects oftechnical‑level factors
Relative advantage is directly associated with attitude
and intention, which is also in accordance with previous
research [43, 44]. Meanwhile, relative advantage figured
the strongest total, direct and indirect effects on inten-
tion, which revealed that physicians’ intentions to use
Table 5 Results of standardized direct, indirect, and total effects
*p < 0.05; **p < 0.01
Paths Direct eects (path
coecients) Indirect eects Total eects
Attitude → Behavioral intention 0.166* 0 0.166*
Subjective norms → Attitude 0.619* 0 0.619*
Subjective norms → Behavioral intention 0.244* 0.103** 0.347**
Perceived risk → Attitude − 0.119* 0− 0.119*
Perceived risk → Behavioral intention − 0.113* − 0.020* − 0.133*
Relative advantage → Attitude 0.368** 0 0.368*
Relative advantage → Top management support 0.454* 0 0.454*
Relative advantage → Behavioral intention 0.307** 0.215* 0.522**
Ease of use → Attitude − 0.050 0− 0.050
Ease of use → Top management support 0.283** 0 0.283**
Ease of use → Behavioral intention – 0.088** 0.088**
Top management support → Organizational implementation 0.797* 0 0.797*
Top management support → Behavioral intention 0.200* 0.140* 0.340*
Organizational implementation → Behavioral intention 0.176* 0 0.176*
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Dengetal. Antimicrob Resist Infect Control (2021) 10:97
CPGs on antimicrobials can be greatly strengthened if
the CPGs on antimicrobials have advantages in improv-
ing clinical efficacy, promoting practice efficiency and
ensuring patients’ safety.
In contrast to expectations, ease of use was not shown
to have a significant influence on attitude, which is dif-
ferent from the findings of Davis and Venkatesh [45, 46].
e plausible reason may be that the role of ease of use
often has no significant effect at the beginning of imple-
mentation, which is similar to the statement proposed
in a previous study [47] that the impact of ease of use is
limit at an early stage of technology uptake. Another pos-
sibility we also can’t rule out is that the impact of ease of
use on attitude was reduced by relative advantage, which
is also included in the final model demonstrating a great
association with ease of use and significant impacts on
attitude.
Eects oforganizational‑level factors
In terms of hospital level, it is reported that physicians’
intentions and utilization of using CPGs on antimicro-
bials were significantly influenced by top management
support [48]. As influential people in the hospitals,
top managers play important roles in developing the
organizational vision and culture, as well as shaping the
expected behavior and norms of physicians [49]. e
support of hospital top managers for the use of CPGs
on antimicrobials is often reflected in the establish-
ment of a series of systems and mechanisms to assess,
motivate and supervise the realization of correspond-
ing goals, which can not only directly stimulate the use
intentions of physicians, but also have an indirect effect
on the intentions through organizational implementation
[50]. In addition to the institutional design, the overall
application of CPGs on antimicrobials in hospitals also
change intentions and further affect the practical use of
physicians. To some extent, top management support
and organizational implementation act as external social
norms, exerting direct or indirect influences on physi-
cians’ behaviors from the outside to the inside, until they
gradually adjust their behaviors to be consistent with the
organization [51].
Policy implications
Based on the understandings of the influencing mecha-
nism of physicians’ intentions to use CPGs on antimicro-
bials, several intervention strategies can be highlighted
for further improving physicians’ intentions and practical
use of CPGs on antimicrobials.
For hospital managers, the use of CPGs on antimicro-
bials by physicians is promoted more through explicit
means such as regulations. Firstly, providing specific
support (e.g., funding, personnel, information, system)
is one of the effective measures to promote physicians’
intentions to use CPGs on antimicrobials. Secondly, the
establishment of feedback and expert panel is indispen-
sable to timely solve various issues of the implementation
of CPGs on antimicrobials. irdly, education and train-
ing are essential for increasing the knowledge of CPGs on
antimicrobials (including the perceptions of usefulness,
ease of use, and so on), as well as to help physicians foster
positive attitudes toward CPGs on antimicrobials and its
use, which can be adopted as long-term strategies [2].
Hospital managers can also advance the use of CPGs on
antimicrobials by physicians in an implicit approach, that
is, by leveraging subjective norms to increase physicians’
intentions to use CPGs on antimicrobials. Specifically,
this means mobilizing influential people for physicians
(generally referred to department directors, authoritative
experts, etc.) to adapt physicians’ compliance with CPGs
on antimicrobials, which is an internalized process.
Strengths andlimitations
To the best of our knowledge, there were very few
national surveys to investigate the related behaviors of
CPGs on antimicrobials among physicians, particularly
in developing countries. is study examined the mech-
anism of physicians’ intentions to use CPGs on antimi-
crobials based on the integration of TPB, TAM and TOE,
which allowed us to systematically consider the factors
associated with the intentions to use CPGs on antimicro-
bials from three levels, namely individual, technical and
organizational determinants.
ere are also some limitations to this study. Firstly, all
the data were obtained by self-reported, we cannot rule
out the social desirability bias [52] that some physicians
may be unwilling to voice negative assessments about
themselves and the hospitals. Secondly, limited to time
and fund, we focus the factors at the individual, techni-
cal, and organizational-level in this study, and the influ-
ence of external environmental factors will be explored
in future research. irdly, considering the limitation of
a cross-sectional study in causality interpretations, future
research may involve sample at different point of time to
form a panel data, which will be more robust in capturing
the influencing factors.
Conclusions
e present study investigated the determinants of the
physicians’ intentions to the utilization of CPGs on anti-
microbials. SEM approach was used to verify the proposed
conceptual research framework. e findings of this study
revealed the significance of multifaceted factors to enhance
the intention to use CPGs on antimicrobials, including atti-
tude, subjective norms, perceived risk, relative advantage,
ease of use, top management support, and organizational
Content courtesy of Springer Nature, terms of use apply. Rights reserved.
Page 9 of 10
Dengetal. Antimicrob Resist Infect Control (2021) 10:97
implementation. ese findings will not only benefit tai-
loring future interventions for expanding the utilization of
CPGs on antimicrobials, but also provide clues for future
research about physicians’ adoption behaviors on certain
health services or products.
Abbreviations
AMR: Antimicrobial resistance; CPGs: Clinical practice guidelines; SEM: Struc-
tural equation modeling.
Supplementary information
The online version contains supplementary material available at https:// doi.
org/ 10. 1186/ s13756- 021- 00966-z.
Additional le1. Questionnaire. The questionnaire represents the data
collection instrument that was developed for this study, hasn’t previously
been published elsewhere.
Additional le2. STROBE_checklist_cross-sectional. The checklist rep-
resents the details of the manuscript, which reports the information that
meets the criteria of STROBE guidelines.
Acknowledgements
We are thankful to all coordinators and physicians for their participation in this
study.
Authors’ contributions
LW designed and conducted the project, contributed to grasp the subject
and revised the manuscript. ZZ, ZY and LJ performed the data curation and
data analysis. DQ carried out the data analysis and drafted the manuscript.
LW and DQ developed the questionnaire. All authors read and approved the
manuscript before submission.
Funding
This research was supported by National Natural Science Foundation of China
(Grant Number: 71704026) and the Soft Science Project of Fujian Provincial
Department of Science and Technology (Grant Number: 2017R0044). No
funders had a role in study design, data collection, data analysis, or in writing
the manuscript.
Availability of data and materials
The datasets generated during and/or analyzed during the current study are
available from the corresponding author on reasonable request.
Declarations
Ethics approval and consent to participate
Ethics approval was obtained from the medical ethics committee, Fujian
Medical University, China. Written informed consent was obtained from all
study participants.
Consent to publish
Not applicable.
Competing interests
The authors declare that they have no competing interests.
Received: 2 November 2020 Accepted: 3 June 2021
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