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Analysis of a Professional Journal Article Submit Assignment

peer review an article

Analysis:
How to do it

Analysis is
written in memo format
State in the memo:
This memo provides an evaluation of an article from a professional journal. The analysis evaluates the visuals, mechanics, organization, and readability of the article as well as whether the author’s research shows evidence of pseudoscience. The analysis will also determine how the scientific method was used.

Analysis is
written in memo format
State in the memo:
The article was found by searching the online database [Name of database] using the keyword [xyz ]
I selected this article because I am pursuing a master’s degree in software engineering and am interested in [what is your interest?]
Overall it is a [good, adequate, etc. article,]
Does it have any weaknesses?

Analysis -Audience
The author’s intended audience appears to be [interested in topic? Experts? But for those without a technical background, the article will be a challenge to read through.]
Through the use of visuals, a good format layout, and clear writing, the authors do a [good, fairly good, adequate] job in communicating

Analysis -Organization
The introduction of the article clearly states the subject, purpose, and scope of the article.
Each paragraph also has a topic sentence that provides a good introduction of the supporting details. For example, when the author discusses xyz, he starts with x, and continues to explain [x]

Analysis -Organization
However, the introduction does not provide a complete outline of the article. For example__the author leaves out information about______. The faults in the introduction provide the reader with a false impression of the flow of the article, possibly leading to confusion and misunderstanding.
Some terms the author mentions are/are not clearly defined. This makes the article more difficult/easier to understand.
Additionally, the article does not have a conclusion. But the article needs a conclusion to summarize important points found throughout the article.

Analysis -Readability
Despite problems with____the rest of the article is organized in a logical manner. (Note the connection to the previous section)
The logical flow makes it easy to read. The author has a unique way of illustrating and providing context for some of the technical terminology [or makes it difficult.]
For example…

Analysis -Formatting
Good formatting aids in providing a good flow for the readers.
Spacing, section headings, a good table of contents, glossary…
For example, the author…

Analysis –Grammar and Mechanics
Good grammar and mechanics also aid in making the article understandable. Why?
Grammatical mistakes are distracting and slow the reader down….
Mistakes also show a lack of credibility and professionalism…
Except for some rare cases in which the writing style shifted from formal to informal, the grammar and mechanics overall were fine…

Analysis –Scientific
Method and Pseudoscience
Although the grammar and mechanics are not exactly precise, the science methodology and data collection appear to be sound. For example…..
To address the research, it is evident the author used the scientific method. For example…
Because the author used the scientific method, there is no evidence of pseudoscience. In addition, the journal’s articles are peer reviewed, and the article would not have been published had the reviews suspected any pseudoscience.

Analysis – Conclusion
[Summarize by mentioning information from the above sections…]
The proper use of visuals, implementation of a professional scientific format, and good readability and formatting work together to create successful publication.
This experience helped me [in what way?] better understand research communication? A key lesson I learned was…

RESEARCH ARTICLE Open Access

Avian influenza A/H7N9 risk perception,
information trust and adoption of
protective behaviours among poultry
farmers in Jiangsu Province, China
Bin Cui1,2, Qiuyan Liao3*, Wendy Wing Tak Lam3, Zong Ping Liu2,4 and Richard Fielding3

Abstract

Background

: Poultry farmers are at high-risk from avian influenza A/H7N9 infection due to sustained occupational
exposures to live poultry. This study examined factors associated with poultry farmers’ adoption of personal
protective behaviours (PPBs) based on Protection Motivation Theory (PMT).

Methods

: Totally, 297 poultry farmers in three cities of Jiangsu Province, China were interviewed during November
2013-January 2014. Data on PMT constructs, perceived trustworthiness of A/H7N9 information from mass media
(formal sources), friends and family (informal sources), intention to adopt and actual adoption of PPBs and
respondents’ demographics were collected. Structural equation modeling (SEM) identified associations between
demographic factors and PMT constructs associated with A/H7N9-oriented PPB intention. Moderated mediation
analysis examined how demographics moderated the effects of information trust on PPB intention via risk
perceptions of A/H7N9.

Results

: Respondents generally perceived low vulnerability to A/H7N9 infection. The SEM found that male
respondents perceived lower severity of (β = −0.23), and lower vulnerability to (β = -0.15) A/H7N9 infection; age
was positively associated with both perceived personal vulnerability to (β = 0.21) and perceived self-efficacy
(β = 0.24) in controlling A/H7N9; education was positively associated with perceived response efficacy (β = 0.40).
Furthermore, perceived vulnerability (β = 0.16), perceived self-efficacy (β = 0.21) and response efficacy (β = 0.67)
were positively associated with intention to adopt PPBs against A/H7N9. More trust in informal information (TII) was
only significantly associated with greater PPB intention through its positive association with perceived response
efficacy. Age significantly moderated the associations of TII with perceived Self-efficacy and perceived response
efficacy, with younger farmers who had greater TII perceiving lower self-efficacy but higher response efficacy.

Conclusion: Poultry farmers perceive A/H7N9 as a personally-irrelevant risk. Interventions designed to enhance
perceived response efficacy, particularly among lower educated respondents may effectively motivate adoption of
PPBs. Informal information may be an important resource for enhancing response efficacy.

Keywords: Influenza A (H7N9), Risk perception, Information trust, Behaviour, Poultry farmers

* Correspondence: qyliao11@hku.hk
3Division of Behavioural Sciences, School of Public Health, The University of
Hong Kong, 21 Sassoon Road, Pokfulam, Hong Kong, Special Administrative
Region, China
Full list of author information is available at the end of the article

© The Author(s). 2017 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0
International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and
reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to
the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver
(http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

Cui et al. BMC Public Health (2017) 17:463
DOI 10.1186/s12889-017-4364-y

http://crossmark.crossref.org/dialog/?doi=10.1186/s12889-017-4364-y&domain=pdf

mailto:qyliao11@hku.hk

http://creativecommons.org/licenses/by/4.0/

http://creativecommons.org/publicdomain/zero/1.0/

Background
The first human cases of avian influenza A (H7N9) were
reported in eastern China in March 2013 [1], subse-
quently spreading to over 10 provinces in China [2]. For-
tunately, the virus transmits inefficiently between
humans [3, 4]. Genomic analysis suggests that A/H7N9
virus is of avian origin and mainly transmitted through
exposure to infected poultry [1]. The median age of
confirmed A/H7N9 human cases was 61 years [3], indi-
cating that older people are a high risk group for A/
H7N9 infection. Over 60% of confirmed A/H7N9 human
cases reported a history of exposure to live poultry [2].
This raises concerns that those in frequent contact with
poultry such as poultry traders and poultry farmers are
at high risk of A/H7N9 infection. Although only 6% of
confirmed A/H7N9 human cases were poultry workers
[3], one previous study reported that over 50% of the
surveyed poultry workers had seroconversion for A/
H7N9 virus from May 2013 to December 2013 in South-
ern China though none had virologically confirmed A/
H7N9 infection [5]. This indicates that people with oc-
cupational exposure to poultry could have a high risk of
mild or asymptomatic A/H7N9 infection. More recently,
one study indicates that poultry farms could be import-
ant sources of reassortment between A/H7N9 virus and
other strains of avian influenza viruses [6]. Therefore,
poultry farmers may have a high risk of A/H7N9
infection.
The “China Animal Industry Yearbook 2011” reports

China having at least 44,061,961 poultry farmers [7].
Large-scale migration in 1990s China saw younger
adults migrate from rural to urban areas becoming fac-
tory workers [8], sharply raising the mean age of the
remaining rural residents with proportions of residents
greater than 60 years increasing from 10.9% in 2000 to
15.0% in 2010 [9]. Therefore, many rural Chinese
poultry farmers are probably older and potentially more
vulnerable to A/H7N9 infection.
Understanding how people at high-risk respond to the

outbreak of this novel influenza can guide public health
interventions. For example, previous studies identified
that an erroneous belief that cooking was the best way
of protection from avian influenza could reassure
continuing buying of live poultry from wet markets the
public [10] and that live poultry traders generally failed
to recognize the risks from contact with bird secretions
or droppings [11]. All these knowledge deficits could be
addressed by public health education to improve pro-
tective behaviours. How people perceive the risk of a
novel influenza appears to partially influence their pro-
tective behaviours [12–14]. However, although the rela-
tionships between risk perception and self-protective
behaviours have been widely examined in many descrip-
tive studies following novel influenza outbreaks, many

are atheoretical [14] and this limits the confidence we
have in the veracity of the findings. A theoretical basis is
important because it generates testable predictions that
build confidence in the validity of the underlying pro-
cesses. Studies suggest that protective behaviours in re-
sponse to newly emerging infectious disease outbreaks
differ by respondents’ socio-demographic characteristics,
particularly age, gender and educational attainment [14]
possibly because these variables influence perception of
risk [15, 16]. However, few studies have tested these hy-
potheses within any theoretical frameworks. Studies of
pandemic influenza A/H1N1 found that older respon-
dents perceived greater severity of, but lower personal
susceptibility to the disease while males generally per-
ceived lower severity of and personal susceptibility to
the disease [15, 17]. Few studies reported the relation-
ships between educational attainment and risk percep-
tion of influenza. However, higher educational level has
been consistently associated with lower perceived risk
from other health threats [18, 19], possibly because
higher educated people are more likely to be unrealistic-
ally optimistic when evaluating their personal risk [19]
which might imply greater personal agency or self-
efficacy [20]. In relation to experience, farmers with
more experience in raising poultry report more familiar-
ity with poultry diseases and thereby perceived lower
risk from avian influenza and higher confidence in pre-
venting the disease [13, 21]. Consequently, the first ob-
jective of this study was to examine how A/H7N9-
related risk perceptions and demographics including
age, gender, educational attainment and working
experience (indicating by years of raising poultry) influ-
enced intention to adopt personal protective behaviours
(PPBs) against A/H7N9. We hypothesized that demo-
graphics influence intention to adopt PPBs against A/
H7N9 through their effects on A/H7N9-related risk
perceptions.
Sources of information are important when consider-

ing threat-related information veracity. We distinguish
between different information sources as follows: Learn-
ing from the experience of the 2003 SARS outbreak in
China, the Chinese government actively disseminated
information about A/H7N9 through traditional mass
media (e.g., TV, radio and newspaper) since it emerged
in China in March 2013 [22–24]. Traditional mass
media in Mainland China are mainly regarded as
government-agency sources for information of infectious
diseases and thereby such information is assumed to
constitute “formal information” in this study. Informa-
tion of A/H7N9 disseminated through media is likely to
provoke widespread public discussion about the topic. In
contrast, information communicated through casual
interpersonal communication between friends and fam-
ily constitutes “informal information” for the purposes of

Cui et al. BMC Public Health (2017) 17:463 Page 2 of 13

this study. Trust is a core element for effective risk com-
munication, particularly for uncertain infection risks
where the risk-related threat is usually invisible [25].
Causal models of trust propose that information trust
influences behavioural change indirectly through alter-
ations in risk perceptions [26–28]. The literature on
trust suggests two main types of trust can be identified;
trust based on judgments of the intentions of others (re-
lational trust) and the trust based on judgments of com-
petence (calculative trust) [29]. While trust in informal
information (TII) approximates to relational trust, trust
in government (formal) information approximates to
calculative trust [29]. Therefore, we propose that trust in
formal and informal information may function di-
fferentially to motivate behavioural change through their
effects on risk perceptions [29]. Previous studies con-
ducted among the general public during the 2009 influ-
enza A/H1N1 pandemic suggests that while trust in
formal information was significantly associated with
perceived confidence in preventing the disease (efficacy
appraisal), TII was significantly associated with perceived
risk of the disease (threat appraisal) [30]. Furthermore,
the degree of trust in health information from various
sources differed by demographics including age, gender
and educational attainment [31]. Therefore, it seems
plausible that demographics including age, gender and
education attainment exert their effects by modifying the
effects of information trust on risk perceptions. Therefore,
the second objective of the current study was to examine
whether demographics including age, gender and educa-
tional attainment could modify the indirect effects of in-
formation trust on intention to take protective behaviours
through risk perceptions related to A/H7N9. Due to lack
of available data, no hypotheses about the direction of the
moderated effects were set for this objective.

Methods
The theoretical framework
This study was designed based on Protection Motivation
Theory (PMT) which has been used successfully to pre-
dict a variety of behaviours [32, 33]. Many studies have
suggested that PMT provides a useful theoretical frame-
work for understanding people’s response to threat-
related information during outbreaks of newly-emerging
respiratory infectious diseases [14, 33]. PMT focuses on
individuals’ cognitive processes in response to fear ap-
peal messages. It proposes that four core cognitive pro-
cesses mediate the effects of fear appeal messages on
motivation to adopt protective behaviours [32]. These
four core cognitive processes are perceived Vulnerability
(i.e. subjective estimates of the chance of contracting a
disease), perceived Severity (i.e., subjective estimates of
the seriousness of a disease), perceived Self-efficacy (i.e.,
the belief that one can successfully take the preventive

behaviours) and perceived Response Efficacy (i.e., the be-
lief that existing preventive behaviours are effective in
reducing risk of the disease) [34]. PMT also predicts that
individual characteristics influence motivation for behav-
ioural change through their effects on these four cogni-
tive components [32]. In this study, we hypothesized
that poultry farmers’ demographics, including gender,
age, educational attainment and years of raising poultry
influence the PMT constructs of perceived Vulnerability
(to A/H7N9), perceived Severity (of A/H7N9), perceived
Self-efficacy and perceived Response Efficacy in control-
ling H7N9, which in turn influence poultry farmers’
intention to adopt PPBs against A/H7N9. Figure 1 out-
lines the conceptual model used. According to the hy-
potheses of PMT, all the four core components, perceived
Vulnerability, perceived Severity, perceived Self-efficacy
and perceived Response Efficacy, are hypothesized to be
positively associated with intention to adopt PPBs.
Due to limited literature on the relationship between

demographics variables and PMT constructs related to
avian influenzas, we hypothesized a model comprising
saturated relationships (testing all possible relationship
permutations) between specified demographic variables
and PMT constructs (Fig. 1). Drawing on prior studies
we hypothesized that females would perceive higher
Vulnerability to and higher Severity of A/H7N9 while
older people would perceive lower Vulnerability to but
higher Severity of A/H7N9; farmers with more years’
experience of raising poultry would perceive lower Vul-
nerability to A/H7N9 and lower Severity of A/H7N9
infection, but perceive higher Self-efficacy and Response
Efficacy in preventing A/H7N9. For other associations
between demographics and PMT constructs, no hypoth-
eses about the directions of associations were set due to
lack of prior data.

Sampling
In the 2013–2014 A/H7N9 outbreak in Mainland China
[35], around 52.3% of the cases were reported from
Zhejiang, Jiangsu and Shanghai, three provinces located
in eastern China along the Yangtze River delta. A total of
59 A/H7N9 human cases had been reported as of
December 31, 2014 in Jiangsu Province, with a fatality
rate of around 29.6% [36]. Around 28.2% of all con-
firmed cases of A/H7N9 between March 2013 and June
2014 in China were farmers and around 6% were poultry
framers or workers [37]. It was estimated that there were
at least 1,094,505 poultry farmers in Jiangsu Province
in 2011 [7]. This study was conducted in three cities
of Jiangsu Province: Suqian, Nantong and Zhenjiang
(Additional file 1: Figure S1).
A/H7N9 virus has been isolated from various birds in-

cluding pigeons, chickens and ducks [38] but viral shed-
ding is higher and more prolonged in quails and

Cui et al. BMC Public Health (2017) 17:463 Page 3 of 13

chickens compared to other species [39]. Considering
that type of poultry may be a factor that influences
poultry farmers’ A/H7N9 risk perceptions and that
chicken is the dominant type of poultry raised by these
poultry farmers, this study only recruited poultry
farmers who raised chickens.
Subjects were recruited using a mixed strategy of

stratified sampling and random sampling (Fig. 2). Firstly,
three prefectural-level cities located in the northern,
central and southern parts of Jiangsu Province respect-
ively were selected. Within each selected prefectural-
level city, two county-level cities were randomly selected
from all those within the prefectural-level city, and
within each county-level city, two county-level districts
were randomly selected. Following this, three villages
were randomly selected from each selected county-level
district. Finally, around 10 poultry farmers within each
selected village were randomly selected according to
the name lists provided by local veterinary authorities

(which must record all licensed poultry farms), and
approached by the trained researcher for the face-to-
face interview. A flow chart showing the process of
sampling was provided (Fig. 2).

Ethics, consent and permissions
This study was conducted during November 2013 to
January 2014 following ethical approval from the
Yangzhou University and local veterinary bureau
which is mainly responsible for distributing avian influ-
enza prevention guideline and monitoring the poultry
health and the health of people who work with poultry in
Mainland China. The target subjects were first given an
explanation of the study and then their consent to partici-
pate was sought. Those agreeing completed a face-to-face
interview using a standardized questionnaire. The ques-
tionnaire was fully anonymous without collecting any
personal identity information. Farmers who were not at
home at the time when they were approached or refused

Fig. 2 The flow chart showing the process of sampling

Fig. 1 The conceptual framework based on Protection Motivation Theory for understanding farmers’ intention to adopt protective behaviours
against avian influenza A/H7N9

Cui et al. BMC Public Health (2017) 17:463 Page 4 of 13

to participate were replaced with their nearest neighbor
poultry farmers, again based on the veterinary authorities’
lists. Each subject who completed the survey was pre-
sented with a small gift (a towel and soap).

Study instrument
A questionnaire was designed to measure major con-
structs of PMT including perceived Vulnerability to and
perceived Severity of A/H7N9, perceived Self-efficacy
and perceived Response Efficacy for protecting against
A/H7N9 infection, the intention to adopt, and actual
adoption of PPBs against A/H7N9 infection, degree of
trust in information about A/H7N9 from traditional
mass media (formal), family and friends (informal)
sources and finally demographics including gender, age,
education and the number of years spent raising poultry.
Specifically, the measures for perceived Severity (4

items), perceived Vulnerability (4 items), perceived Self-
efficacy (4 items), perceived Response Efficacy (4 items),
and protective intention (3 items) were adapted from
earlier pre-validated studies [40–42]. For these items,
the respondents were asked to indicate on a 7-point
Likert-type scale their level of agreement or disagree-
ment with each statement in the questionnaire (ranging
from “1 = very strongly disagree” to “7 = very strongly
agree”). The measure of actual PPBs included seven
questions that asked respondents if they had adopted
each of seven protective behaviours (wearing gloves,
wearing protective clothes, wearing a face mask, wearing
a protective hat, wearing protective shoes, washing
hands after touching dead poultry, washing hands after
touching poultry feces (Yes/No)) in their routine hus-
bandry practices. Protective behaviour adoption was
recorded as “1”. Otherwise, “0” was recorded. These
seven protective behaviours are recommended by the
National Health and Family Planning Commission of
China in their proposal for personal protection against
highly pathogenic avian influenza for high risk persons
including the poultry workers and farmers, aiming to
reduce their risk of contracting avian influenza viral
infection due to occupational exposure to poultry [43].
Two items, each assessing trust in information about A/
H7N9 from formal (e.g., how much do you trust the in-
formation about A/H7N9 influenza from newspaper, TV
and radio?) and informal sources (e.g., how much do
you trust the information about A/H7N9 influenza from
you friends or relatives?), respectively, were measured
with a 5-point Likert-type scale (ranging from “1 = do
not believe” to “5 = fully believe”). Items for measuring
the PMT constructs and basic descriptive data were
shown in Additional file 2: Table S1.
The questionnaire was pretested for its comprehen-

sibility and length among 45 chicken farmers from a
country of Suqian city in October 2013 before being

formally used in the survey. Minor amendments were
made for items that were not easily understood by the
farmers but the original meanings of the items were
retained.

Data analysis
To assess the reliability and validity of measures for the
PMT constructs including perceived Vulnerability to and
perceived Severity of A/H7N9 infection, perceived Self-
efficacy and Response Efficacy for preventing A/H7N9
and intention to adopt PPBs against A/H7N9, Cron-
bach’s alpha (α) coefficients for each latent variable were
first calculated. All α values exceeded 0.80 (Additional
file 2: Table S2), indicating high internal consistency
(internal reliability) for the measures [44]. Then, the
average variance extracted (AVE) was used to assess the
validity of all these scales. A value of AVE greater than
0.5 for a latent variable indicates a good convergent
validity for that variable [45]. The results showed that
the AVE values of all PMT constructs exceeded 0.80,
suggesting high convergent validity for these latent vari-
ables. Using the Fornell–Larcker criterion, the square
root of all AVE values (the diagonal values in Additional
file 2: Table S2) were higher than the correlations
between all latent variables (off-diagonal values) indicat-
ing that each latent variable shares more variance with
its assigned indicators than with any other latent vari-
able. Such results suggest good discriminant validity for
each latent variable.
The conceptual model (Fig. 1) was tested using struc-

tural equation modelling (SEM) with demographic
variables entered into the model as observed covariant
variables and PMT constructs entered as latent variables.
All covariance, factor loadings, measurement errors, dis-
turbances and path coefficients were estimated using
robust maximum likelihood (MLR) estimator [45]. Path
coefficients with p-values less than 0.05 were considered
as statistically significant. Multiple model fit indices
including CFI, TLI, RMSEA and SRMR was used to assess
the global model fit. Values of CFI and TLI great than 0.9,
of RMSEA and SRMR less than 0.8 suggest an acceptable
fit of the model to data. The local fit of the model was
assessed by investigating the residual matrix. Since the
model was run with MLR estimator, the Satorra-Bentler
scaled chi-square difference test [46] was used to compare
nested models in order to identify the optimal and more
parsimonious model. The direct effects of risk perceptions
and indirect effects of demographic on Intention to adopt
protective behaviours through risk perceptions were cal-
culated using Bootstrapping methods.
To assess whether the effects of information trust on

Intention to take protective behaviours through A/
H7N9-related risk perceptions could be modified by age,
gender and educational attainment, two analytic steps

Cui et al. BMC Public Health (2017) 17:463 Page 5 of 13

were adopted. First, we tested the simple mediation
model which hypothesized that the effect of information
trust on Intention to take protective behaviours was me-
diated by perceived Severity, perceived Vulnerability,
perceived Self-efficacy and perceived Response efficacy.
Once the simple mediation relationship was established,
multiple group modelling was conducted to examine the
conditional indirect effect for each moderator (i.e., gen-
der, age and education). Bootstrapping methods were
used to calculate the 95% confidence interval of specific
conditional indirect effects. Significant difference in
conditional indirect effects across stratum of the mod-
erator indicates significant moderated effect on the me-
diation relationship. All analyses were conducted using
Mplus 7.0.

Results
The participants
A total of 297 respondents were recruited from 360
poultry farmers approached, a response rate of 82.5%.
All respondents completed the face-to-face interview
based on the questionnaire without missing data. These
297 chicken farmers fed between 300 and 25,000 chick-
ens (median = 4000) each. Policy changes in Jiangsu
Province encourage large-scale poultry farming while
discouraging small-scale backyard poultry husbandry in
order to increase the management standards of rural
poultry farming. Of the respondents, 76.1% were male,
while 50.8% and 30.6% were aged 46–55 years and
≥56 years, respectively; 76.1% of the respondents
attained junior high school or lower educational achieve-
ment and over half (56.6%) had raised chickens for at
least 10 years (Table 1).

A/H7N9 risk perceptions, intention to adopt and actual
adoption of PPBs against A/H7N9
Respondents generally reported low perceived Vulnerabil-
ity to A/H7N9 (mean value = 2.32 possible range 1–7)
while perceived Severity of A/H7N9 was high (mean
value = 5.96 possible range 1–7) (Additional file 2:
Table S1). Perceived Self-efficacy was also high (mean
value = 5.75 possible range 1–7) while perceived
Response Efficacy (mean value = 4.81 possible range
1–7) and intention to adopt PPBs against A/H7N9
(mean value = 4.91 possible range 1–7) were moder-
ate (Additional file 2: Table S1).
Actual adherence to recommendations for washing

hands after touching poultry feces (99.7%, 296/297),
washing hands after touching dead poultry (89.9%, 267/
297) and wearing protective clothing during poultry
husbandry (87.9%, 261/297) were highly prevalent (Fig.
3). Only one third of respondents (32.3%, 96/297) wore
face masks during routine husbandry practices and
20.5% (61/297) wore protective shoes. Around 12.5%
(37/297) of the respondents adopted all the seven
recommended protective behaviours. We ran a multi-
variate logistic model to regress adoption of all seven
recommended protective behaviours on age, gender,
educational attainment and years of raising poultry. The
results showed that after adjustment for other de-
mographics, respondents who had higher educational
attainment were more likely to adopt all the seven
recommended protective behaviours (Reference group:
Primary or below; OR = 10.06, 95%CI: 2.08-48.62 for
junior high school; OR = 9.53, 95%CI: 1.68-54.04 for
senior high school or above), while respondents who
had raised poultry for 10–20 years were less likely to
adopt all the seven recommended protective behaviours
(OR = 0.04, 95%CI: 0.01-0.20) relative to respondents
who had raised poultry for less than 10 years.

Relationships among demographics, PMT constructs and
intention to adopt PPBs
The hypothesized model was initially run with all paths
from demographic variables to PMT constructs freely es-
timated (Model I). Then all insignificant paths (p ≥ 0.05)
from the demographics to the PMT constructs were re-
moved and the revised model (Model II) was re-run.
Compared with Model I, Model II had comparable
model fit indices, and the Satorra-Benter scaled chi-
square difference test suggests that it fits to the data as
well as Model I (Table 2). However, investigation of the
residual matrix identified significant residual covariance
between perceived Vulnerability and perceived Self-
efficacy, between perceived Vulnerability and perceived
Response Efficacy, between perceived Self-efficacy and
perceived Severity, and between perceived Self-efficacy
and perceived Response Efficacy. It indicates that the

Table 1 Respondents’ characteristics (N = 297)

Characteristics N %

Gender

Female 71 23.9%

Male 226 76.1%

Age

≦45 years 55 18.5%

46-55 years 151 50.8%

> 55 years 91 30.6%

Education

primary or below 73 24.6%

Junior high school 153 51.5%

Senior high school or above 71 23.9%

Years raising poultry

≦10 years 129 43.4%

10- 20 years 123 41.4%

> 20 years 45 15.2%

Cui et al. BMC Public Health (2017) 17:463 Page 6 of 13

residual covariance of these latent variables is correlated.
Therefore, the covariance between these variables was
added to the model. The re-specified model (Model III) fits
the data significantly better than Model II (Table 2). Investi-
gation of the residual matrix revealed no significant residual
covariance between the variables of Model III. Therefore,
Model III was determined to be the optimal model.
Compared with Model II, the parameters estimated for the
structural part of Model III only differ slightly. The correla-
tions between the four demographics age, gender, educa-
tional attainment and years of raising poultry were not
higher than 0.33 (spearman correlation between age and
gender), suggesting that multicollinearity is not a significant
problem of the model [47]. The standardized covariance,
path coefficients and the explained variance of each en-
dogenous variable for Model III are shown in Fig. 4.
Gender was significantly associated with perceived Sever-

ity (β = −0.23) and perceived Vulnerability (β = -0.15), with
female respondents perceiving higher Severity of, and Vul-
nerability to A/H7N9 infection than did males (Fig. 4). Age
was significantly and positively associated with both per-
ceived Vulnerability to A/H7N9 (β = 0.21) and perceived
Self-efficacy (β = 0.24) in controlling A/H7N9. Educational
attainment was only significantly and positively associated

with perceived Response Efficacy (β = 0.40) while years of
raising poultry were negatively associated with perceived
Response Efficacy (β = -0.10). Subsequently, perceived
Vulnerability to A/H7N9 (β = 0.16), perceived Self-efficacy
(β = 0.21) and Response Efficacy (β = 0.67) were positively
associated with Intention to adopt protective behaviours
against A/H7N9. However, perceived Severity of A/H7N9
was not significantly associated with protective Intention,
which is inconsistent with PMT predictions. The model
explained 50.7% of the variance in Intention to adopt PPBs
but only explained 5.5%, 6.4%, 5.7% and 17.0% Perceived
Severity, Perceived Vulnerability, Perceived Self-efficacy
and Perceived Response Efficacy, respectively.
The unstandardized direct effects of risk perceptions,

and indirect effects of demographics via risk perceptions
on Intention to adopt PPBs including the point estimate
and 95% Bootstrapping confidence interval are shown in
Table 3. Perceived Response Efficacy had strongest effect
on behavioural Intention (point estimate = 0.54, 95%CI:
0.47-0.63). While education (point estimate = 0.35, 95%CI:
0.27-0.45) and age (point estimate = 0.11, 95%CI:
0.05-0.18) had significant positive indirect effects, gender
and years of raising poultry did not had significant indirect
effects on behavioural Intention (Table 3).

Fig. 3 Actual adoption of personal protective behaviours against A/H7N9 among the respondents

Table 2 Comparison of model fit indices of Model I, Model II and Model III

Nested models χ2 (df) Scaling correction factor CFI TLI RMSEA (90% CI) χ2 difference test (p)

Model I 495.03 (148) 1.12 0.94 0.93 0.09 (0.08-0.10) –

Model II 499.87 (158) 1.12 0.94 0.93 0.08 (0.08-0.09) p>0.10

Model III 420.69 (154) 1.13 0.96 0.95 0.08 (0.07-0.08) p<0.001

Model II is nested within Model I and Model III
Compared with Model I, Model II removed the paths from gender to Perceived Self-efficacy and Perceived Response efficacy, from Age to Perceived Severity and
Perceived Response efficacy, from Education to Perceived Severity, Perceived Vulnerability and Perceived Self-efficacy, and from years of raising poultry to
Perceived Severity, Perceived Vulnerability and Perceived Response efficacy
Compared with Model II, Mode III added covariance for the relationships of Perceived Vulnerability with Perceived Self-efficacy and Perceived Response efficacy,
and the relationships of Perceived Self-efficacy with Perceived Severity and Perceived Response efficacy

Cui et al. BMC Public Health (2017) 17:463 Page 7 of 13

Fig. 4 The results of structural equation model for understanding determinants on intention to adopt protective behaviours against A/H7N9
based on Protection Motivation Theory. a p<,0.05, b p < 0.01, c p < 0.001. The numbers on the paths are standardized path coefficient; the dotted line indicates the effect is not statistically significant

Table 3 The direct effects of risk perceptions and indirect effects of demographics on Intention to adopt personal protective behaviours
via risk perceptions

Effects by exogenous variables

Point estimate (SE) Bootstrapping (95%CI)

Lower Upper

Direct effects

Perceived Severity→Intention -0.03 (0.03) -0.08 0.03

Perceived Vulnerability→Intention 0.11 (0.04)b 0.04 0.18

Perceived Self-efficacy→Intention 0.40 (0.09)c 0.23 0.58

Perceived Response Efficacy→Intention 0.54 (0.04)c 0.47 0.63

Indirect effects

Gender→Intention

Via Perceived Severity 0.02 (0.02) -0.02 0.06

Via Perceived Vulnerability -0.05a -0.11 −0.01

Total -0.03 (0.03) -0.10 0.02

Age→Intention

Via Perceived Vulnerability 0.04 (0.02)a 0.01 0.09

Via Perceived Self-efficacy 0.07 (0.02)b 0.03 0.12

Total 0.11 (0.03)c 0.05 0.18

Education→Intention

Via Perceived Response
Efficacy

0.35 (0.04)c 0.27 0.45

Years of raising→Intention

Via Perceived Response
Efficacy

-0.08 (0.04) -0.17 -0.00

ap < 0.05, bp < 0.01, cp < 0.001; SE: Standard Error

Cui et al. BMC Public Health (2017) 17:463 Page 8 of 13

Information trust and the moderated effects of
demographics on the relationships between information
trust and PMT constructs
As shown in Table 4, over 99% (275/297) of respondents
indicated mostly or completely trusting information from
formal sources (TV, radio or newspaper). In contrast, only
14.5% (43/297) of respondents reported mostly or com-
pletely trusting informal information (information from
friends or relatives). Male respondents and those with
higher educational achievement were more likely to trust in
formal or informal information compared with their coun-
terparts (Table 4). Information trust did not differ by age
and years of raising poultry. The universally high level of
trust in formal information complicates testing for the
moderated mediation models due to almost zero data

variability. Therefore, the analysis only focused on the mod-
erated effects of demographics on the relationships of TII
with behavioural Intention via risk perceptions of A/H7N9.
The simple mediation model which hypothesized that

effect of TII on Intention to adopt PPBs was mediated by
perceived Severity, perceived Vulnerability, perceived Self-
efficacy and perceived Response Efficacy were first tested.
The simple mediation model fit well to the data (CFI=0.97,
TLI=0.97, RMSEA=0.08 (90%CI: 0.07-0.09)). The results
(Table 5) showed that only the indirect effects of TII on
Intention through perceived Response Efficacy was signifi-
cant (point estimate=0.57, 95%CI: 0.39-0.77).
Then multiple group modelling with each moderator

being treated as a grouping variable was conducted to cal-
culate and compare the indirect effects of TII on Intention

Table 4 Trust in formal and informal information by demographic characteristics

Demographic characteristics Trust in formal information Trust in informal information

Trust (mostly/completely trustworthy) P-valuea Trust (mostly/completely trustworthy) P-valueb

Gender

Female (69/71) 97.2% 0.011 (4/71) 5.6% 0.015

Male (226/226)100% (39/226) 17.3%

Age

≦45 years (55/55) 100% 0.804 (4/55) 7.3% 0.241

46-55 years (149/151) 98.7% (24/151) 15.9%

≧56 years (91/91) 100% (15/91) 16.5%

Education

Primary or below (71/73) 97.3% 0.043 (7/73) 9.6% <0.001

Junior high school (153/153) 100% (14/153) 9.2%

Senior high school or above (71/71) 100% (22/71) 31.0%

Years raising poultry

≦10 years (127/129) 98.4% 0.153 (12/129) 9.3% 0.080

≦20 years (123/123) 100% (22/123) 17.9%

≧21 years (45/45) 100% (9/45) 20.0%
aFisher Exact test
bPearson chi-square

Table 5 The direct and indirect effects of trust in informal information on Intention to adopt personal protective behaviours based
on the simple mediation model

Point estimate (SE) Bootstrapping (95%CI)
Lower Upper

Direct effect -0.04 (0.13) -0.28 0.24

Indirect effect

Via perceived Severity -0.01 (0.01) -0.04 0.01

Via perceived Susceptibility 0.01 (0.02) -0.02 0.07

Via perceived Self-efficacy -0.07 (0.04) -0.17 -0.00

Via perceived Response Efficacy 0.57 (0.10)c 0.39 0.77

Total indirect effect 0.50 (0.09)c 0.33 0.69

Total effect 0.46 (0.16)b 0.15 0.75
b p<0.01, c p<0.001

Cui et al. BMC Public Health (2017) 17:463 Page 9 of 13

via risk perceptions of A/H7N9 (Table 6). It shows that the
indirect effects of TII on Intention via perceived Severity
and Vulnerability were not significant across stratum of
gender, age group and educational achievement. The indir-
ect effect of TII on Intention via perceived Self-efficacy was
only significant for female (point estimate=-0.24, 95%CI:
-0.52–-0.06) and younger farmers (point estimate=-0.16,
95%CI: -0.30–-0.07). Age significantly moderated the medi-
ation of TII with Intention via perceived Self-efficacy, with
younger farmers who had more trust in informal informa-
tion perceived lower self-efficacy. The indirect effects of TII
on Intention via perceived Response Efficacy were signifi-
cant across stratum of gender, age group and educational
achievement excepting for framers who were older than 55
years. Age significantly moderated the mediation of TII
with Intention via perceived Response Efficacy, with youn-
ger farmers who had more trust in informal information
perceived higher response efficacy.

Discussion

Based on PMT, our study investigated how cognitive
processes mediated the effects of demographics on
motivation to adopt protective behaviours against A/
H7N9, and how information trust interacted with demo-
graphics to influence A/H7N9 protection among the
Chinese poultry farmers.
Generally, the study found that the respondents

perceived A/H7N9 infection to be severe but did not per-
ceive themselves to be vulnerable to the infection. This is
consistent with one previous study conducted in The
Netherlands which found that over 90% of the respondents
perceived that avian influenza was a serious disease (mean
score = 4.57, scale 1–5) but only 0.7% of them perceived
themselves to be highly vulnerable to avian influenza (mean
score = 1.69, scale 1–5) [48]. Chinese poultry farmers
report more familiarity with poultry disease risk than do
urbanites and are more optimistic about avoiding avian
influenzas [12, 13]. Both familiarity and optimistic bias
probably further account for the low perceived Vulnerabil-
ity observed among these Jiangsu poultry farmers.

All PMT constructs were positively associated with
PPB intention except for perceived Severity of A/H7N9
which was not significantly associated with PPB intention.
The meta-analysis on the efficacy of PMT also indicates
that the effect size of perceived Severity on protection
motivation was the smallest among the four PMT
constructs [32]. Given the small-to-moderate effect size of
perceived Severity on behavioral intention, our small
sample size may not be able to detect a significant
association. However, while a previous review indicated that
Self-efficacy had the strongest effect on behavioral intention
[32], our study found that perceived Response Ef-
ficacy had the strongest effect on PPB intention,
accounting for nearly 50% of the explained variance
in PPB intention. For these poultry farmers, perceived
Self-efficacy to adopt the preventive measures was gener-
ally high possibly because the recommended preventive
measures are simple and thereby easily adopted. In this
case, whether the preventive measures are believed to
be effective or not to reduce risk of A/H7N9 plays a
dominant role in determining their motivation to
adopt the measures.
The finding that respondents with higher educational

achievement had better compliance to PPBs is consistent
with a previous study reporting better educated poultry
traders were more likely to adopt PPBs when working [49].
Our study adds to the literature about the potential mech-
anism of how education influence adoption of PPBs. As in-
dicated by the SEM, better educated respondents perceived
higher response efficacy to prevent A/H7N9 which in turn
was associated with higher intention to adopt protective be-
haviours against A/H7N9. Compared with other de-
mographics, education had stronger indirect effects on
intention to adopt protective behaviours via Perceived Re-
sponse Efficacy. This suggests that interventions to pro-
mote belief in the efficacy of available protective behaviours
among the less educated farmers may play a crucial role to
improve compliance to self-protection against A/H7N9.
Consistent with our hypotheses, our study also found

that females perceived higher personal Vulnerability to

Table 6 The estimated conditional indirect effects of trust in informal information on intention to adopt personal protective
behaviours against influenza A/H7N9 via risk perceptions

Moderator Level Conditional indirect effects of TII on Intention (Bootstrapping 95% CI) via:

Perceived Severity Perceived Vulnerability Perceived Self-efficacy Perceived Response efficacy

Gender Female 0.04 (-0.03, 0.13) -0.16 (-0.39, 0.10) -0.24 (-0.52, -0.06)a 0.30 (0.16-0.49)b

Male -0.02 (-0.08, 0.00) 0.05 (0.00, 0.15) -0.05 (-0.17, 0.00) 0.56 (0.33, 0.80)c

Age group (years) ≦55 -0.01 (-0.04, 0.01) 0.02 (-0.02, 0.07) -0.16 (-0.30, -0.07)b 0.77 (0.53, 1.00)c

>55 -0.02 (-0.14, 0.04) -0.03 (-0.21, 0.11) 0.05 (-0.03, 0.19) 0.19 (-0.10, 0.44)

Education Junior middle or below -0.02 (-0.08, 0.01) -0.01 (-0.09, 0.06) 0.08 (-0.01, 0.26) 0.25 (0.01, 0.41)a

Senior high or above -0.00 (-0.07, 0.05) 0.08 (0.01, 0.29) 0.04 (-0.16, 0.27) 0.54 (0.23, 0.91)b

a p<0.05, b p<0.01, c p<0.001; SE: Standard Error The bold values indicate that effects were significant different across stratum of a moderator

Cui et al. BMC Public Health (2017) 17:463 Page 10 of 13

A/H7N9 and higher Severity of A/H7N9 compared with
males. This finding may elucidate why compliance to
recommended protection was usually higher among
females during epidemics found in many descriptive
studies [14]. However, the associations between age and
PMT constructs were not consistent with our hypoth-
eses. According to the SEM, older respondents perceived
higher Vulnerability to A/H7N9 and higher Self-efficacy
to prevent against A/H7N9 which in turn was signifi-
cantly associated with higher intention to adopt PPBs.
However, our study did not find a significant association
between age and compliance to the recommended pro-
tective measures. This suggests factors other than these
four PMT constructs may hinder translating the intention
of adopting PPBs into actual behaviours among the older
respondents. For example, perceived costs from taking the
recommended behaviours (e.g., effort, time) may be
greater among older people (e.g. older people need to take
greater effort to alter their long-term habit) [32].
Our initial hypotheses that years of working with

poultry could be associated with lower perceived Vulner-
ability and perceived Severity but higher perceived Self-
efficacy and Response Efficacy were not supported. Years
of working with poultry were only marginally associated
with perceived Response Efficacy but the effect size
was small. One possible reason could be that our
measure of years of working with poultry may not be
a good indicator for farmer’s experience with raising
poultry. While a previous study did not find significant
association between years of working with poultry and
adoption of protective behaviours [11], our study found that
respondents who had raised poultry for 10–20 years were
less likely to adopt all the recommended protective mea-
sures than those who had raised poultry for less than
10 years after adjusting for age and educational attainment.
Further studies are needed to explore the relationship
between experience with poultry and adoption of PPBs
among poultry farmers.
The indirect effect of TII on Intention to adopt PPBs

was only significant via perceived Response Efficacy,
with greater TII being associated with greater perceived
Response Efficacy which was positively associated with
behavioural Intention. This is not consistent with one
previous study that TII was independent of efficacy be-
lief but was positively associated with disease worry [30].
A possible reason for the inconsistent results could be
that the former study was conducted among general public
[30] while the current study was conducted among poultry
farmers. Different types of informal information are prob-
ably communicated among different populations. Farmers
may simply know what kinds of protective behaviours are
available for preventing A/H7N9 through listening to their
peer farmers and observing what they do. Age significantly
moderated the mediation relationships of TII with

behavioural Intention through perceived Self-efficacy and
Response Efficacy. For younger farmers, more trust in in-
formation from peers was associated with perceived lower
Self-efficacy but higher Response Efficacy, while corre-
sponding associations were not statistically significant for
older farmers. Such findings provide some insights about
the possible types of information shared among younger
poultry farmers. Younger poultry farmers who are usually
better educated may be more aware of the effectiveness of
available preventive measures in reducing risk of A/H7N9
but they may lack of confidence in adopting these prevent-
ive measures due to lack of skills in routine husbandry
practices with protective measures. For example, they may
find it more inconvenient to wear gloves or protective
clothes in their routine husbandry practice. Therefore, it
may be important to provide training for improving young
poultry farmers’ skills of taking protective measures.
This study has several limitations. First, the cross-

sectional design excluded causal inference. Second, with-
out follow-up data, this study cannot examine the gap
between intention and subsequent adoption of PPBs,
though current adherence to PPBs was measured, and
past behaviour is the best predictor for future behaviours
[50]. Third, actual PPBs were dichotomously (yes/no)
measured and because of social desirability bias, may
provide less accurate assessment of actual compliance.
Furthermore, while multilevel SEM (MSEM) may be
more appropriate for our data that were collected based
on sampling stratified by clusters, MSEM cannot be
conducted due to lack of data on clusters. Therefore,
our single-level SEM assuming that subjects were in-
dependent within clusters may underestimate the
sampling variance, which may result in inflation of
the type I error [45].

Conclusions

Jiangsu poultry farmers generally perceived A/H7N9
Severity as high, but personal Vulnerability to infection
as low, these variables being weakly associated with
intention to adopt PPBs, possibly due to perceived
personally-irrelevant risk. The moderate perceived Re-
sponse Efficacy of respondents and its strongest associ-
ation with PPB intention reflect that interventions
designed to enhance perceived Response Efficacy may
effectively motivate adoption of PPBs among these poultry
farmers. Education appears to influence intention to adopt
PPBs through its positive association with Response
Efficacy, suggesting that Response Efficacy should be
promoted among lower educated farmers. For example,
information about how and why a recommended behavior
can eliminate or decrease risk of infection should be
clearly presented and framed in an easily-understood way
for lower educated framers. The study also adds to the
literature that gender appears to influence on intention to

Cui et al. BMC Public Health (2017) 17:463 Page 11 of 13

adopt PPBs through its effects on perceived disease Vul-
nerability and Severity, while age may influence on behav-
ioural intention through its effects on perceived disease
Vulnerability and perceived Self-efficacy in prevention.
Greater TII was associated with higher Intention to take
protective measures through its positive association with
perceived Response Efficacy. Age significantly moderated
the association between TII and perceived Self-efficacy,
and between TII and perceived Response Efficacy, with
younger farmers who had greater TII perceived lower
Self-efficacy but higher Response Efficacy. Young poultry
farmers may just simply obtain the information about the
availability of effective preventive measures against A/
H7N9 from listening to what their peer farmers say and
observing what they do. This suggests that interventions
utilizing farmer peers to communicate and train poultry
farmers in taking protective measures during routine hus-
bandry practice may be effective to promote adoption of
PPBs among poultry farmers.

Additional files

Additional file 1: Figure S1. Map of Jiangsu Province showing the
sampling sites. Note: Maps of China and Jiangsu Province were
reproduced based on maps provided by WIKIPEDIA available from
https://en.wikipedia.org/wiki/Jiangsu (TIFF 1511 kb).

Additional file 2: Table S1. and S2. The measuring items for the
constructs of Protection Motivation Theory and descriptive statistics
(DOCX 25 kb).

Additional file 3: Data for analysis (XLS 163 kb).

Abbreviations

AVE: Average variance extracted; PMT: Protection Motivation Theory;
PPBs: Personal protective behaviours; SEM: Structural equation modeling;
TII: Trust in Informal Information

Acknowledgements

Not applicable.

Availability of data and materials

The data for this paper are available in the Additional file 3.

Funding

This research was funded by the National Natural Science Foundation of
China (Grant no: 71,573,221).

Authors’ contributions

BC designed the study, collected the data, analyzed the data and
drafted the manuscript. QL analyzed the data, guided data
interpretation, drafted and revised the manuscript. WWTL advised on
data interpretation and revised the manuscript. ZPL participated in the
study design and coordination, and revised the manuscript. RF advised
on data analysis and data interpretation, and revised the manuscript.
All authors read and approved the final manuscript.

Competing interests

The authors declare that they have no competing interests.

Consent for publication

Not applicable.

Ethics approval and consent to participate

This study received ethical approval from the Yangzhou University and
local veterinary bureau which is mainly responsible for monitoring the
poultry health and health of the people who work with poultry in
Mainland China. All participants gave oral consent to participate in the
study before the interview started.

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in
published maps and institutional affiliations.

Author details

1Business College, Yangzhou University, Jiangsu Province, China. 2Jiangsu
Co-innovation Center for Prevention and Control of Important Animal
Infectious Diseases and Zoonoses, Yangzhou, China. 3Division of Behavioural
Sciences, School of Public Health, The University of Hong Kong, 21 Sassoon
Road, Pokfulam, Hong Kong, Special Administrative Region, China. 4College
of Veterinary medicine, Yangzhou University, Jiangsu Province, People’s
Republic of China.

Received: 28 January 2016 Accepted: 3 May 2017

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Analysisof a Professional Journal Article for readability
Assignment

Updated 10/13/

020

Assignment due: October 20, 2020

Assignment length: a full 2-3 pages, single spaced, blank line between paragraphs. Maximum

. No longer than that

Memorandum format (Markel text, Chapter 15).

Percentage of course grade: 10%

Where do we begin?
The library presentation (discussed in class) is the beginning of the Analysis of a Professional Journal Article for Readability assignment. The engineering librarian discussed the basic services available at the library and showed you the engineering-oriented databases.

This demo is important for this assignment and can be very helpful in your other engineering classes. During the library demo, you had an opportunity to explore some scholarly journals and possibly pick the one that has the article for your analysis.

What’s next?

The assignment asks you to select and analyze a professional journal article from a high quality peer-reviewed journal** on a topic related to your team’s final project. You will determine if:

It is it a readable technical document, and

The authors use a valid scientific approach to substantiate their claims.

You will select a journal with a publication date between 2014-2019.

Note the differences between professional journals and trade magazines. This makes a difference in trusting the validity of the data. The librarian will also help us with this.

Our textbook (Markel) will be a helpful resource to your professional journal article analysis for “readability” and “writing qualities”.

The Martin Luther King Library will also help with understanding scientific methods–real science. Topics include:

Secondary Research

Evaluating Print and Online Sources

Scientific Method

As you start this assignment:

Determine the article’s main topic and get a general idea of what it is about and how it is organized. Make a note of what the article’s purpose is and the article’s intended audience.

Next, look at your technical writing text (Chapters 17, 18, 19) and determine what the author summarizes as the criteria for a good report. Then read the article carefully, and while you are reading it, annotate where the author uses strategies to convey his/her message.

Consider these questions: Is the article well organized? Is there proper grammar and punctuation? Are there tables, charts, and graphs? Are they helpful? Are other visual aids needed?

Analyze the introduction, the main discussion, and the terminal section for the validity of the content. Analyze the document to determine if the reasoning is based on pseudoscience, or ‘junk’ science versus real science (examples in lecture and text). Provide examples in your memo. More than likely, articles from professional technical journals apply scientific methodologies. Note how the authors do this.

Write a formal memo to your instructor with your evaluation.

You need an introduction

For clarity, use subject headings

Do not restate or summarize the contents of the article; focus on the specific analysis and incorporate specific evidence (quotations) to illustrate your points.

Are the purpose and audience properly addressed? Your memo has two major sections (readability/writing qualities and scientific methodologies). For scientific methodologies:

a. Briefly explain the scientific method or the design process used in the article. Markel’s text will help with understanding scientific methods and real science. See Markel’s Experiments showing the scientific method: p. 134. Cunningham’s Principles of Environmental Science will also be helpful. See section 1.4 “Science helps us understand our world” and section 1.5 “Critical thinking.”

b. Briefly explain pseudoscience. Use critical thinking, and check for pseudoscience versus real science (examples in lecture and text). Discuss why this article is not pseudoscience. Provide examples in your report..

Remember, you need a conclusion/recommendation
When you have evaluated the report and searched for the strong and weak points, you should be better prepared to write and evaluate your own reports in the future. Would this be a good professional journal for you to submit an article that you have written?

Give the journal article reference at the bottom of your memo in APA format.* (See also, section in Markel text)

The memo must be submitted to Canvas.

*APA Documentation

WHY APA for documentation and references?

More engineering schools now use APA rather than the other formats. (However, many professors use

IEEE

or MLA.) Always go to your audience and use what they want. Most non-EE advisors now want APA for the following reasons.

With cut and paste and rearranging articles, you never lose the citation, which can happen when you forget what, for example, #8 or #10 was. You always know when it says (Jones, 2012).

When you use a numbering system, you have to provide a number in the back for each one. If you use a source 12 times, it will have 12 different numbers in the back. If you use APA, it is just stated once in the back, alphabetically.

Approximately 94% of the audience never looks in the back for the notes or references. In APA, the audience immediately sees the author and the date. The date is important in engineering and technical writing–to make sure the information is current.

Sample Journal Article References in APA:

Journal article (hard copy)

Linsdell, J., & Anagnos, T. (2011) Motivating technical writing through study of the environment,

Journal of Professional Issues in Engineering Education and Practice

, ASCE, 137, 20-27.

Journal article (viewed online, retrieved electronically, with no DOI assigned. DOI stands for digital object identifier.)

Srivastava, R. K., & More, A. T. (2010). Some aesthetic considerations for over-the- counter (OTC) pharmaceutical products. International Journal of Biotechnology, 11(3-4), 267-283. Retrieved from http://www.inderscience.com

Journal article preprint version of article with DOI assigned

Wang, T. J., Larson M. G., Vasan, R. S., & Gerszten, R.E. (2011). Metabolite profiles and the risk of developing diabetes. Nature Medicine. Advance online publication, doi:10.1038/nm.2307

**Short List of Examples of Professional Technical Journals (There are over 15,000 professional journals — find one that meets your research needs.

(Librarian will have more information about this.)

American Society of Mechanical Engineers

Journal of Electronic Packaging

Journal of Fuel Cell Science and Technology

Journal of Mechanical Design

Journal of Solar Energy Engineering

Journal of Computing and Information Science in Engineering

Journal of Applied Mechanics

Association of Computer Engineers and Technicians Computer Science and Engineering Society American Society of Civil Engineers

Journal of Professional Issues in Engineering Education and Practice

American Institute for Medical and Biological Engineering (AIMBE)

Journal of Medical Devices

International Journal of Biotechnology Institute of Industrial Engineers American Society of Safety Engineers

Association for Computing Machinery (Journal of the ACM) ACM Transactions on Software Engineering Methodology American Institute of Aeronautics and Astronautics

AIAA Journal

Journal of Aerospace Computing, Information, and Communication

Journal of Guidance, Control, and Dynamics

Journal of Spacecraft and Rock

American Association for Artificial Intelligence

Artificial Intelligence Journal

IEEE

IEEE Transactions on Circuits and Systems for Video Technology

IEEE Transactions on Components and Packaging Technologies

IEEE Transactions on Consumer Electronics

IEEE Transactions on Electron Devices

IEEE Transactions on Software Engineering

IEEE Transactions on Wireless Communications

IEEE Transactions on Visualization and Computer Graphics

Society of Manufacturing Engineers (e.g., Journal of Manufacturing Systems)

Chemical Engineering

Journal of Chemical Engineering and Materials Science

Canadian Society for Chemical Engineering (CSChE)

Journal of Composite Materials

Reminder:

Plagiarism will result in a grade of F. Papers with plagiarism cannot be rewritten for credit. You can check for plagiarism with Turnitin.com

[Simple memo format]

To: XXXXXX

From: Student

Subject: Analysis of a Professional Journal

Date: XXX, XX, 2011

[Provide an introduction to the analysis paper

Use section headings

Paragraphs are single-spaced with a space in between. Font is 12 point. Min 2 pages, Max 3 pages.]

Introduction

[Which article are you evaluating? Where was it published and who are the authors? When was it published?]

I am evaluating a journal article entitled: The face of success inferences from chief executive officers’ appearance predict company profits. [note only first word capitalized. No italics or quotes.]The article was published in Psychological Science, [note journal title is in italics] in February 2008. [note no comma after February. But if you write February 14, 2008 you need a comma to separate the day 14 from the year 2008.] The authors of the article are Nicholas O. Rule and Nalini Ambady from Tufts University.

Evaluation [This is the analysis and critique of the journal article]

The purpose of this article is to present results of a short study done at Tufts University. The study investigated whether or not there is evidence that a company’s success can be predicted based purely on the subjective looks of the CEO. The article is directed mainly at the psychological science community, but also possibly intended to grab the attention of interested investors looking for a way to predict the future success of a candidate investment. [Previous sentence describes audience.]The article is written at an appropriate level for the science community, but there are some places where the meanings of certain statistical variables are not explained. This may not be sufficient for casual readers who may be interested in the article as well. [Provides critique about whether authors achieved the goal of reaching described audience.]

The article is well organized and the well-labeled sections follow a logical progression. Beginning with a brief introduction that grabs the attention of the reader, the authors also provide background on previous related work. They also explain why the study in the article is unique and important. [Provides critique about introduction, structure of article. The student says there’s background on previous related work. Do you notice if there is a literature review?]

Next, the article follows with a detailed description of the methods used, explaining how the experiment was set up and why it was designed as it was. It was in this section, however, that several statistical variables were introduced without a definition for what they mean. The science community is familiar with these variables, so for them this is not a problem. However readers without a science background may be left without a good understanding. [Provides critique about methods and difficulty of understanding variables.]

In terms of grammar, punctuation and style, the authors have done a good job . However, some of the figures presented in the document are not clear. For instance, the formatting on the table of results appears to be confusing and difficult to read. It shows text headings on the vertical axis but only numbers on the horizontal axis. The author has, however, placed the word “Measure” is in the upper left hand corner. This is confusing because some readers may interpret the horizontal numbers to be the measure values that were used in the experiment. This is especially the case, because only four lines before the table, the authors write that the tests were conducted using a seven-point scale, and the numbers on the horizontal axis of the table are labeled one through six. Furthermore, some entries of the table are left blank, and the authors don’t provide the reader with a clear explanation as to why. Finally, in the note below the table, there are more statistical variables that are used without being defined in the article.

[Provides critique about methods.]The statistical methods applied to the data are scientific, however, the experiment as a whole leaves more work to be done. This is appropriate, because the authors do not claim that their results are definitive, but rather that they have shown some evidence of the conclusions they have. One improvement that could add to the scientific value is increasing the number of companies tested as well as the range of the companies’ successes. Fifty companies were used, but all of them were in the Fortune 1000, so all were highly successful. More scientific conclusions could be made if a full range of companies was tested, including companies that have failed. The experiment may also be more scientifically significant with a wider range of evaluators. The tests were done with only undergraduate college students ranging in age from 18 to 22. Greater statistical significance could be achieved with more subjects over a wider age range. Still, the correlation numbers that were measured were very high in several cases, allowing the authors to justifiably claim significant evidence in their findings.

[Provides critique about possible pseudoscience .]One aspect of the study that may be considered pseudoscience is the way in which the CEOs’ physical attributes were measured. The measurements were very subjective, essentially the opinions of the test subjects. Furthermore, it may be the case that companies that make more money simply pay for more expensive photographers to take the pictures of the CEOs that will be published online. This would also explain a high correlation between highly rated CEO photos and companies’ financial success. Additionally, these photos may have been taken after the companies were already successful. It would have been a good idea to ensure that all CEO photos were taken before the companies achieved their revenues and profits. This would strengthen the argument that the companies’ success could have been “predicted” by the photos.

Conclusion

[Provides overall conclusion and what could be improved.] In all, most of the article is well written and informative for scientific readers as well as readers of casual interest. The experiment was a short study, but the results appear to be statistically significant. The authors claim an appropriate level of significance by stating only that their results show evidence of an effect. Again, the writing style is well organized and grammatically correct. The content is presented in a logical order, but more definition and explanation of variables could help a non-scientific reader. However, since this article was published in a psychological science journal, however, the authors’ objectives were successfully met.

Only one reference at end of paper, in APA Style. Make sure the style is correct for the journal article you analyzed.

Reference

Rule, N. O., & Ambady, N. (2008). The Faces of Success Inferences From Chief Executive Officers’ Appearance Predict Company Profits. Psychological Science, 19(2), 109-111. doi:10.1111/j.1467-9280.2008.02054.x

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